Metabolic Reprogramming of Sulfur in Hepatocellular Carcinoma and Sulfane Sulfur-Triggered Anti-Cancer Strategy

Based on disulfidptosis-related glycolytic genes to construct a signature for predicting prognosis and immune infiltration analysis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) comprises several distinct molecular subtypes with varying prognostic implications. However, a comprehensive analysis of a prognostic signature for HCC based on molecular subtypes related to disulfidptosis and glycolysis, as well as associated metabolomics and the immune microenvironment, is yet to be fully explored.

Methods

Based on the differences in the expression of disulfide-related glycolytic genes (DRGGs), patients with HCC were divided into different subtypes by consensus clustering. Establish and verify a risk prognosis signature. Finally, the expression level of the key gene SLCO1B1 in the signature was evaluated using immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) in HCC. The association between this gene and immune cells was explored using multiplex immunofluorescence. The biological functions of the cell counting kit-8, wound healing, and colony formation assays were studied.

Results

Different subtypes of patients have specific clinicopathological features, prognosis and immune microenvironment. We identified seven valuable genes and constructed a risk-prognosis signature. Analysis of the risk score revealed that compared to the high-risk group, the low-risk group had a better prognosis, higher immune scores, and more abundant immune-related pathways, consistent with the tumor subtypes. Furthermore, IHC and qRT-PCR analyses showed decreased expression of SLCO1B1 in HCC tissues. Functional experiments revealed that SLCO1B1 overexpression inhibited the proliferation, migration, and invasion of HCC cells.

Conclusion

We developed a prognostic signature that can assist clinicians in predicting the overall survival of patients with HCC and provides a reference value for targeted therapy.

Mechanism of homocysteine-mediated endothelial injury and its consequences for atherosclerosis

Homocysteine (Hcy) is an intermediate amino acid formed during the conversion from methionine to cysteine. When the fasting plasma Hcy level is higher than 15 μmol/L, it is considered as hyperhomocysteinemia (HHcy). The vascular endothelium is an important barrier to vascular homeostasis, and its impairment is the initiation of atherosclerosis (AS). HHcy is an important risk factor for AS, which can promote the development of AS and the occurrence of cardiovascular events, and Hcy damage to the endothelium is considered to play a very important role. However, the mechanism by which Hcy damages the endothelium is still not fully understood. This review summarizes the mechanism of Hcy-induced endothelial injury and the treatment methods to alleviate the Hcy induced endothelial dysfunction, in order to provide new thoughts for the diagnosis and treatment of Hcy-induced endothelial injury and subsequent AS-related diseases.

The double-edged role of hydrogen sulfide in the pathomechanism of multiple liver diseases

In mammalian systems, hydrogen sulfide (H₂S)-one of the three known gaseous signaling molecules in mammals-has been found to have a variety of physiological functions. Existing studies have demonstrated that endogenous H₂S is produced through enzymatic and non-enzymatic pathways. The liver is the body's largest solid organ and is essential for H₂S synthesis and elimination. Mounting evidence suggests H₂S has essential roles in various aspects of liver physiological processes and pathological conditions, such as hepatic lipid metabolism, liver fibrosis, liver ischemia‒reperfusion injury, hepatocellular carcinoma, hepatotoxicity, and acute liver failure. In this review, we discuss the functions and underlying molecular mechanisms of H₂S in multiple liver pathophysiological conditions.

Vitamin B6 Metabolic Pathway is Involved in the Pathogenesis of Liver Diseases via Multi-Omics Analysis

Purpose

To clarify the underlying regulatory mechanisms of progression from liver cirrhosis to hepatocellular carcinoma (HCC), we analyzed the microbiomics, metabolomics, and proteomics in plasma and tissues from patients with HCC or decompensated liver cirrhosis (DC).

Patients and Methods

Tissues and plasma from 44 HCC patients and 28 patients with DC were collected for metabolomic analysis. 16S rRNA sequencing was performed in nine HCC tissues (HCCT), four distal noncancerous tissues (HCCN), and 11 DC tissues (DCT). Five HCC tissues had liver cirrhosis (HCCT-LC). Five hepatocellular carcinoma tissues without liver cirrhosis (HCCT-NLC) and five DCT were selected for proteomic sequencing. After combining proteomic and metabolomic analysis, we constructed a mouse model of chronic liver injury using carbon tetrachloride (CCl4) and treated them with vitamin B6 (VB6).

Results

16s rRNA sequence results showed that HCC tissues had higher alpha diversity. The highest LDA scores were detected for Elizabethkingia in HCCT, Subsaxibacter in DCT, and Stenotrophomon in HCCN. Metabolomics results demonstrated some metabolites, including capric acid, L-threonate, choline, alpha-D-Glucose, D-ribose, betaine, 2E-eicosenoic acid, linoleic acid, L-palmitoylcarnitine, taurodeoxycholic acid, L-pyroglutamic acid, androsterone sulfate, and phthalic acid mono-2-ethylhexyl ester (MEHP), had better diagnostic efficacy than AFP (AUC: 0.852; 95% CI: 0.749, 0.954). In a combined analysis of metabolomics and proteomics, we found that HCCT-LC had more obvious disorders of VB6 metabolism and pentose and glucuronate interconversions than DCT, and kynurenine metabolism disorder was more significant in HCCT-LC than in HCCT-NLC. In the CCl4-induced chronic liver injury model, after VB6 supplementation, inflammatory cell infiltration, hepatocyte edema, and degeneration were significantly improved.

Conclusion

We found significant differences in the flora distribution between HCCT and DC; MEHP was a new diagnostic biomarker of HCC, and VB6 ameliorated the inflammatory cell infiltration, hepatocyte edema, and degeneration in chronic liver injury.

Differential OAT methylation correlates with cell infiltration in tumor microenvironment and overall survival post-radiotherapy in oral squamous cell carcinoma patient

BACKGROUND

Given that DNA methylation and tumor microenvironment (TME) are susceptible to radiotherapy, we aimed to figure out specific differential DNA methylation to reflect oral squamous cell carcinoma (OSCC) prognosis and associated effect on TME changes post-radiotherapy, performing as an efficient biomarker.

MATERIALS AND METHODS

Differentially methylation analysis was performed using data from TCGA. Curves of Kaplan Meier (K-M) survival, cumulative hazard and events, Cox proportional hazards and Linear regression model were conducted to screen and validate differential methylation genes, while multiple regression equation to analyze if ornithine aminotransferase (OAT) methylation correlates with radiotherapy. For correlation between OAT methylation and immune infiltrates, CIBERSORT and ESTIMATE algorithms were performed, following GSEA and ssGSEA analysis to evaluate biological process.

RESULTS

Compared to normal tissues, only OAT in OSCC was differential significantly by K-M analysis (p = 0.0364). OAT hypermethylation was associated with increased overall survival (HR: 0.65, p = 0.0358). Radiotherapy correlated with OAT methylation (β = -0.01, p = 0.0061); most patients with OAT hypermethylation were radiation-sensitive. Hypomethylated OAT correlated with higher cell infiltrations in TME. Neuroactive ligand-receptor interaction was most significantly related to OAT methylation (p = 9.2e-10). Sulfur metabolism was the most significantly in OAT hypermethylation group (p = 0.0041) and RIG-I-like receptor in OAT hypomethylation group (p = 0.0094).

CONCLUSION

OAT methylation can serve as a predictor of OSCC prognosis post-radiotherapy with potential mechanism by changing cell infiltrations in TME, but further experimental study deserves to carry out confirming the role and mechanism of OAT methylation in OSCC. This article is protected by copyright. All rights reserved.

Kernel-based hierarchical structural component models for pathway analysis

MOTIVATION

Pathway analyses have led to more insight into the underlying biological functions related to the phenotype of interest in various types of omics data. Pathway-based statistical approaches have been actively developed, but most of them do not consider correlations among pathways. Because it is well known that there are quite a few biomarkers that overlap between pathways, these approaches may provide misleading results. In addition, most pathway-based approaches tend to assume that biomarkers within a pathway have linear associations with the phenotype of interest, even though the relationships are more complex.

RESULTS

To model complex effects including nonlinear effects, we propose a new approach, Hierarchical structural CoMponent analysis using Kernel (HisCoM-Kernel). The proposed method models nonlinear associations between biomarkers and phenotype by extending the kernel machine regression and analyzes entire pathways simultaneously by using the biomarker-pathway hierarchical structure. HisCoM-Kernel is a flexible model that can be applied to various omics data. It was successfully applied to three omics datasets generated by different technologies. Our simulation studies showed that HisCoM-Kernel provided higher statistical power than other existing pathway-based methods in all datasets. The application of HisCoM-Kernel to three types of omics dataset showed its superior performance compared to existing methods in identifying more biologically meaningful pathways, including those reported in previous studies.

AVAILABILITY AND IMPLEMENTATION

Freely available at http://statgen.snu.ac.kr/software/HisCom-Kernel/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.