Identification and validation of EPHX2 as a prognostic biomarker in hepatocellular carcinoma

The role of soluble epoxide hydrolase in the intestine

The soluble epoxide hydrolase (sEH; encoded by the EPHX2 gene) is an α/β hydrolase fold protein that is, widely distributed throughout the body. Recent studies have highlighted that sEH, in the metabolism of polyunsaturated fatty acids, plays a part in the pathogenesis of various diseases, including cardiovascular disease, Alzheimer's disease and intestine-associated disease. This review discusses the current findings on the role of sEH in the development of intestine- and intestine-associated diseases, including colitis, colorectal cancer, and other intestinal diseases, as well as the potential underlying mechanisms involved.

Deciphering the multifaceted role of microRNAs in hepatocellular carcinoma: Integrating literature review and bioinformatics analysis for therapeutic insights

Hepatocellular carcinoma (HCC) poses a significant global health challenge, necessitating innovative therapeutic strategies. MicroRNAs (miRNAs) have emerged as pivotal regulators of HCC pathogenesis, influencing key processes such as self-renewal, angiogenesis, glycolysis, autophagy, and metastasis. This article integrates findings from a comprehensive literature review and bioinformatics analysis to elucidate the role of miRNAs in HCC. We discuss how dysregulation of miRNAs can drive HCC initiation, progression, and metastasis by modulating various signaling pathways and target genes. Moreover, leveraging high-throughput technology and bioinformatics tools, we identify key miRNAs involved in multiple cancer hallmarks, offering insights into potential combinatorial therapeutic strategies. Through our analysis considering p-values and signaling pathways associated with key features, we unveil miRNAs with simultaneous roles across critical cancer characteristics, providing a basis for the development of high-performance biomarkers. The microRNAs, miR-34a-5p, miR-373-3p, miR-21-5p, miR-214-5p, miR-195-5p, miR-139-5p were identified to be shared microRNAs in stemness, angiogenesis, glycolysis, autophagy, EMT, and metastasis of HCC. However, challenges such as miRNA stability and delivery hinder the translation of miRNA-based therapeutics into clinical practice. This review underscores the importance of further research to overcome existing barriers and realize the full potential of miRNA-based interventions for HCC management.

Harnessing Porphyrin Accumulation in Liver Cancer: Combining Genomic Data and Drug Targeting

The liver, a pivotal organ in human metabolism, serves as a primary site for heme biosynthesis, alongside bone marrow. Maintaining precise control over heme production is paramount in healthy livers to meet high metabolic demands while averting potential toxicity from intermediate metabolites, notably protoporphyrin IX. Intriguingly, our recent research uncovers a disrupted heme biosynthesis process termed 'porphyrin overdrive' in cancers that fosters the accumulation of heme intermediates, potentially bolstering tumor survival. Here, we investigate heme and porphyrin metabolism in both healthy and oncogenic human livers, utilizing primary human liver transcriptomics and single-cell RNA sequencing (scRNAseq). Our investigations unveil robust gene expression patterns in heme biosynthesis in healthy livers, supporting electron transport chain (ETC) and cytochrome P450 function without intermediate accumulation. Conversely, liver cancers exhibit rewired heme biosynthesis and a massive downregulation of cytochrome P450 gene expression. Notably, despite diminished drug metabolism, gene expression analysis shows that heme supply to the ETC remains largely unaltered or even elevated with patient cancer progression, suggesting a metabolic priority shift. Liver cancers selectively accumulate intermediates, which are absent in normal tissues, implicating their role in disease advancement as inferred by expression analysis. Furthermore, our findings in genomics establish a link between the aberrant gene expression of porphyrin metabolism and inferior overall survival in aggressive cancers, indicating potential targets for clinical therapy development. We provide in vitro proof-of-concept data on targeting porphyrin overdrive with a drug synergy strategy.

Upregulated Nuclear Expression of Soluble Epoxide Hydrolase Predicts Poor Outcome in Breast Cancer Patients: Importance of the Digital Pathology Approach

Breast cancer (BC) is the most common cancer in women, with incidence rates increasing globally in recent years. Therefore, it is important to find new molecules with prognostic and therapeutic value to improve therapeutic response and quality of life. The polyunsaturated fatty acids (PUFAs) metabolic pathway participates in various physiological processes, as well as in the development of malignancies. Although aberrancies in the PUFAs metabolic pathway have been implicated in carcinogenesis, the functional and clinical relevance of this pathway has not been well explored in BC. To evaluate the clinical significance of soluble epoxide hydrolase (EPHX2) expression in Mexican patients with BC using tissue microarrays (TMAs) and digital pathology (DP). Immunohistochemical analyses were performed on 11 TMAs with 267 BC samples to quantify this enzyme. Using DP, EPHX2 protein expression was evaluated solely in tumor areas. The association of EPHX2 with overall survival (OS) was detected through bioinformatic analysis in public databases and confirmed in our cohort via Cox regression analysis. Clear nuclear expression of EPHX2 was identified. Receiver operating characteristics (ROC) curves revealed the optimal cutoff point at 2.847062 × 10-3 pixels, with sensitivity of 69.2% and specificity of 67%. Stratification based on this cutoff value showed elevated EPHX2 expression in multiple clinicopathological features, including older age and nuclear grade, human epidermal growth factor receptor 2 (HER2) and triple negative breast cancer (TNBC) subtypes, and recurrence. Kaplan-Meier curves demonstrated how higher nuclear expression of EPHX2 predicts shorter OS. Consistently, multivariate analysis confirmed EPHX2 as an independent predictor of OS, with a hazard ratio (HR) of 3.483 and a 95% confidence interval of 1.804-6.724 (p < 0.001). Our study demonstrates for the first time that nuclear overexpression of EPHX2 is a predictor of poor prognosis in BC patients. The DP approach was instrumental in identifying this significant association. Our study provides valuable insights into the potential clinical utility of EPHX2 as a prognostic biomarker and therapeutic target in BC.

Discovery of the sEH Inhibitor Epoxykynin as a Potent Kynurenine Pathway Modulator

Disease-related phenotypic assays enable unbiased discovery of novel bioactive small molecules and may provide novel insights into physiological systems and unprecedented molecular modes of action (MMOA). Herein, we report the identification and characterization of epoxykynin, a potent inhibitor of the soluble epoxide hydrolase (sEH). Epoxykynin was discovered by means of a cellular assay monitoring modulation of kynurenine (Kyn) levels in BxPC-3 cells upon stimulation with the cytokine interferon-γ (IFN-γ) and subsequent target identification employing affinity-based chemical proteomics. Increased Kyn levels are associated with immune suppression in the tumor microenvironment and, thus, the Kyn pathway and its key player indoleamine 2,3-dioxygenase 1 (IDO1) are appealing targets in immuno-oncology. However, targeting IDO1 directly has led to limited success in clinical investigations, demonstrating that alternative approaches to reduce Kyn levels are in high demand. We uncover a cross-talk between sEH and the Kyn pathway that may provide new opportunities to revert cancer-induced immune tolerance.

Enhancing cancer immunotherapy via inhibition of soluble epoxide hydrolase

Cancer therapy, including immunotherapy, is inherently limited by chronic inflammation-induced tumorigenesis and toxicity within the tumor microenvironment. Thus, stimulating the resolution of inflammation may enhance immunotherapy and improve the toxicity of immune checkpoint inhibition (ICI). As epoxy-fatty acids (EpFAs) are degraded by the enzyme soluble epoxide hydrolase (sEH), the inhibition of sEH increases endogenous EpFA levels to promote the resolution of cancer-associated inflammation. Here, we demonstrate that systemic treatment with ICI induces sEH expression in multiple murine cancer models. Dietary omega-3 polyunsaturated fatty acid supplementation and pharmacologic sEH inhibition, both alone and in combination, significantly enhance anti-tumor activity of ICI in these models. Notably, pharmacological abrogation of the sEH pathway alone or in combination with ICI counter-regulates an ICI-induced pro-inflammatory and pro-tumorigenic cytokine storm. Thus, modulating endogenous EpFA levels through dietary supplementation or sEH inhibition may represent a unique strategy to enhance the anti-tumor activity of paradigm cancer therapies.

Heat stress alters the ovarian proteome in prepubertal gilts

Heat stress (HS) occurs when exogenous and metabolic heat accumulation exceeds heat dissipation; a thermal imbalance that compromises female reproduction. This study investigated the hypothesis that HS alters the ovarian proteome and negatively impacts proteins engaged with insulin signaling, inflammation, and ovarian function. Prepubertal gilts (n = 19) were assigned to one of three environmental groups: thermal neutral with ad libitum feed intake (TN; n = 6), thermal neutral pair-fed (PF; n = 6), or HS (n = 7). For 7 d, HS gilts were exposed to 12-h cyclic temperatures of 35.0 ± 0.2 °C and 32.2 ± 0.1 °C, while TN and PF gilts were housed at 21.0 ± 0.1 °C. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed on ovarian protein homogenates. Relative to TN gilts, 178 proteins were altered (P ≤ 0.05, log2foldchange ≥ 1) by HS, with 76 increased and 102 decreased. STRING gene ontology classified and identified 45 biological processes including those associated with chaperone protein refolding, cytoplasmic translational initiation, and immune activation; with a protein-protein interaction web network of 158 nodes and 563 edges connected based on protein function (FDR ≤ 0.05). Relative to PF, HS altered 330 proteins (P ≤ 0.05, log2foldchange ≥ 1), with 151 increased and 179 decreased. Fifty-seven biological pathways associated with protein function and assembly, RNA processing, and metabolic processes were identified, with a protein-protein interaction network of 303 nodes and 1,606 edges. Comparing HS with both the TN and PF treatments, 72 ovarian proteins were consistently altered by HS with 68 nodes and 104 edges, with biological pathways associated with translation and gene expression. This indicates that HS alters the ovarian proteome and multiple biological pathways and systems in prepubertal gilts; changes that potentially contribute to female infertility.

A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults, with an unfavourable outcome and a high rate of recurrence due to its heterogeneity. Dysregulation of fatty acid metabolism plays a crucial role in the development of several tumours. However, the value of fatty acid metabolism (FAM) in the progression of AML remains unclear. In this study, we obtained RNA sequencing and corresponding clinicopathological information from the TCGA and GEO databases. Univariate Cox regression analysis and subsequent LASSO Cox regression analysis were utilized to identify prognostic FAM-related genes and develop a potential prognostic risk model. Kaplan-Meier analysis was used for prognostic significances. We also performed ROC curve to illustrate that the risk model in prognostic prediction has good performance. Moreover, significant differences in immune infiltration landscape were found between high-risk and low-risk groups using ESTIMATE and CIBERSOT algorithms. In the end, differential expressed genes (DEGs) were analyzed by gene set enrichment analysis (GSEA) to preliminarily explore the possible signaling pathways related to the prognosis of FAM and AML. The results of our study may provide potential prognostic biomarkers and therapeutic targets for AML patients, which is conducive to individualized precision therapy.

Wide-spread enhancer effect of SNP rs2279590 on regulating epoxide hydrolase-2 and protein tyrosine kinase 2-beta gene expression

Polymorphisms in the PTK2B-CLU locus have been associated with various neurodegenerative disorders including pseudoexfoliation glaucoma, Alzheimer's and Parkinson's. Many of these genomic variants are within enhancer elements and modulate genes associated with the disease pathogenesis. However, mechanisms by which they control the gene expression is unknown. Previously, we have shown that clusterin enhancer element surrounding rs2279590 intronic variant, a risk factor in the pathogenesis of pseudoexfoliation glaucoma modulates gene expression of clusterin (CLU), protein tyrosine kinase 2 beta (PTK2B) and epoxide hydrolase 2 (EPHX2). Here, we explored the mechanism by which rs2279590 enhancer regulates their gene expression through chromosome conformation capture assays. 3C assays revealed a strong enhancer-promoter chromatin interaction between rs2279590 enhancer and promoters of genes CLU, PTK2B and EPHX2 in the HEK293 wild type cells. Moreover, genomic knockout of rs2279590 element significantly decreases the chromatin-chromatin cross-linking frequency suggesting gene regulation at transcriptional level through formation of chromatin loop. In addition, molecular assays showed a significantly decreased expression of EPHX2 but not PTK2B at both mRNA and protein level in the lens capsule of pseudoexfoliation affected patients in comparison to control subjects implying a role of EPHX2 in the pathogenesis of pseudoexfoliation.

scBPGRN: Integrating single-cell multi-omics data to construct gene regulatory networks based on BP neural network

The deterioration and metastasis of cancer involve various aspects of genomic changes, including genomic DNA changes, epigenetic modifications, gene expression, and other complex interactions. Therefore, integrating single-cell multi-omics data to construct gene regulatory networks containing more omics information is of great significance for understanding the pathogenesis of cancer. In this article, an algorithm integrating single-cell RNA sequencing data and DNA methylation data to construct a gene regulatory network based on the back-propagation (BP) neural network (scBPGRN) is proposed. This algorithm uses biweight extreme correlation coefficients to measure the correlation between factors and uses neural networks to calculate generalized weights to construct gene regulation networks. Finally, the node strength is calculated to identify the genes associated with cancer. We apply the scBPGRN algorithm to hepatocellular carcinoma (HCC) data. We construct a regulatory network and identify top-ranked genes, such as MYCBP, KLHL35, PRKCZ, and SERPINA6, as the key HCC-related genes. We analyze the top 100 genes, and the HCC-related genes are concentrated in the top 20. In addition, the single cell data is found to consist of two subpopulations. We also apply scBPGRN to two subpopulations. We analyze the top 50 genes in them, and the HCC-related genes are concentrated in the top 20. The consequences of functional enrichment analysis indicate that the gene regulatory network we have constructed is valid. Our results have been verified in several pieces of literature. This study provides a reference for the integration of single-cell multi-omics data to construct gene regulatory networks.

Metabolomics- and systems toxicology-based hepatotoxicity mechanism of Sophorae Tonkinensis Radix et Rhizoma in rats

Drug-induced liver injury (DILI) is a major challenge to the development and clinical application of drugs, especially limits the global application of Chinese herbal medicines, because the material basis and mechanisms of some Chinese herbal medicines are not well clear. In this study, a comprehensive method integrating metabolomics and systems toxicology (SysT) was used to investigate how the main substances in Sophorae TonkinensisRadix et Rhizoma (STRER) influence the metabolic pathways and molecular mechanisms of hepatotoxicity. Through a 28-day continuous oral administration toxicity study combined with serum metabolomics analyses, the aqueous, ethanol-precipitation and dichloromethane extracts of STRER exhibited significant hepatotoxic effects. In addition, 19 differential metabolites with a time-dose-effect relationship were identified in rats. The primary bile acid biosynthesis pathway was significantly altered, which was consistent with the findings of the SysT analysis. Furthermore, through the quantification of bile acids in serum, 16 differential bile acids were identified as being significantly changed; moreover, 21 relevant targets which intersected with the hepatotoxic targets of STRER were identified. Molecular docking was used to confirm the validation of bindings between targets and corresponding compounds, and finally, six important compounds and 14 potential targets were identified to be involved in STRER-induced liver injury in relation to bile acid metabolism.

Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network

Purpose

This study was aimed at identifying hub genes and ceRNA regulatory networks linked to prognosis in hepatocellular carcinoma (HCC) and to identify possible therapeutic targets.

Methods

Differential expression analyses were performed to detect the differentially expressed genes (DEGs) in the four datasets (GSE76427, GSE6764, GSE62232, and TCGA). The intersected DEmRNAs were identified to explore biological significance by enrichment analysis. We built a competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA. The mRNAs of the ceRNA network were used to perform Cox and Kaplan-Meier analyses to obtain prognosis-related genes, followed by the selection of genes with an area under the curve >0.8 to generate the random survival forest model and obtain feature genes. Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes. Finally, the infiltration status of immune cells in the HCC samples was determined.

Results

A total of 1923 intersected DEmRNAs were identified in four datasets and involved in cell cycle and carbon metabolism. ceRNA network was created using 10 lncRNAs, 67 miRNAs, and 1,923 mRNAs. LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2. Among them, TMEM106C, LARS, and KPNA2 had a poor prognosis. KPNA2 was considered a key gene base on LASSO and Cox analyses and involved in the ceRNA network. T helper 2 cells and T helper cells showed a higher degree of infiltration in HCC.

Conclusion

The findings revealed seven hub genes implicated in HCC prognosis and immune infiltration. A corresponding ceRNA network may help reveal their potential regulatory mechanism.

A metabolic reprogramming-related prognostic risk model for clear cell renal cell carcinoma: From construction to preliminary application

Metabolic reprogramming is one of the characteristics of clear cell renal cell carcinoma (ccRCC). Although some treatments associated with the metabolic reprogramming for ccRCC have been identified, remain still lacking. In this study, we identified the differentially expressed genes (DEGs) associated with clinical traits with a total of 965 samples via DEG analysis and weighted correlation network analysis (WGCNA), screened the prognostic metabolism-related genes, and constructed the risk score prognostic models. We took the intersection of DEGs with significant difference coexpression modules and received two groups of intersection genes that were connected with metabolism via functional enrichment analysis. Then we respectively screened prognostic metabolic-related genes from the genes of the two intersection groups and constructed the risk score prognostic models. Compared with the predicted effect of clinical grade and stage for ccRCC patients, finally, we selected the model constructed with genes of ABAT, ALDH6A1, CHDH, EPHX2, ETNK2, and FBP1. The risk scores of the prognostic model were significantly related to overall survival (OS) and could serve as an independent prognostic factor. The Kaplan-Meier analysis and ROC curves revealed that the model efficiently predicts prognosis in the TCGA-KIRC cohort and the validation cohort. Then we investigated the potential underlying mechanism and sensitive drugs between high- and low-risk groups. The six key genes were significantly linked with worse OS and were downregulated in ccRCC, we confirmed the results in clinical samples. These results demonstrated the efficacy and robustness of the risk score prognostic model, based on the characteristics of metabolic reprogramming in ccRCC, and the key genes used in constructing the model also could develop into targets of molecular therapy for ccRCC.

Deciphering the role of predicted miRNAs of polyomaviruses in carcinogenesis

Human polyomaviruses are relatively common in the general population. Polyomaviruses maintain a persistent infection after initial infection in childhood, acting as an opportunistic pathogen in immunocompromised populations and their association has been linked to carcinogenesis. A comprehensive understanding of the underlying molecular mechanisms of carcinogenesis in consequence of polyomavirus infection remains elusive. However, the critical role of viral miRNAs and their potential targets in modifying the transcriptome profile of the host remains largely unknown. Polyomavirus-derived miRNAs have the potential to play a substantial role in carcinogenesis. Employing computational approaches, putative viral miRNAs along with their target genes have been predicted and possible roles of the targeted genes in many significant biological processes have been obtained. Polyomaviruses have been observed to target intracellular signal transduction pathways through miRNA-mediated epigenetic regulation, which may contribute to cancer development. In addition, BKPyV-infected human renal cell microarray data was coupled with predicted target genes and analysis of the downregulated genes indicated that viruses target multiple signaling pathways (e.g. MAPK signaling pathway, PI3K-Akt signaling pathway, PPAR signaling pathway) in the host as well as turning off several tumor suppression genes (e.g. FGGY, EPHX2, CACNA2D3, CDH16) through miRNA-induced mechanisms, assuring cell transformation. This study provides a conceptual framework for the underlying molecular mechanisms involved in the course of carcinogenesis upon polyomavirus infection.

EPHX2 Inhibits Colon Cancer Progression by Promoting Fatty Acid Degradation

Tumor cells use metabolic reprogramming to keep up with the need for bioenergy, biosynthesis, and oxidation balance needed for rapid tumor division. This phenomenon is considered a marker of tumors, including colon cancer (CRC). As an important pathway of cellular energy metabolism, fatty acid metabolism plays an important role in cellular energy supply and oxidation balance, but presently, our understanding of the exact role of fatty acid metabolism in CRC is limited. Currently, no lipid metabolism therapy is available for the treatment of CRC. The establishment of a lipidmetabolism model regulated by oncogenes/tumor suppressor genes and associated with the clinical characteristics of CRC is necessary to further understand the mechanism of fatty acid metabolism in CRC. In this study, through multi-data combined with bioinformatic analysis and basic experiments, we introduced a tumor suppressor gene, EPHX2, which is rarely reported in CRC, and confirmed that its inhibitory effect on CRC is related to fatty acid degradation.