Identification and Validation of an 6-Metabolism-Related Gene Signature and Its Correlation With Immune Checkpoint in Hepatocellular Carcinoma

Comprehensive characterization of β-alanine metabolism-related genes in HCC identified a novel prognostic signature related to clinical outcomes

Hepatocellular carcinoma (HCC) stands out as the most prevalent type of liver cancer and a significant contributor to cancer-related fatalities globally. Metabolic reprogramming, particularly in glucose, lipid, and amino acid metabolism, plays a crucial role in HCC progression. However, the functions of β-alanine metabolism-related genes (βAMRGs) in HCC remain understudied. Therefore, a comprehensive evaluation of βAMRGs is required, specifically in HCC. Initially, we explored the pan-cancer landscape of βAMRGs, integrating expression profiles, prognostic values, mutations, and methylation levels. Subsequently, scRNA sequencing results indicated that hepatocytes had the highest scores of β-alanine metabolism. In the process of hepatocyte carcinogenesis, metabolic pathways were further activated. Using βAMRGs scores and expression profiles, we classified HCC patients into three subtypes and examined their prognosis and immune microenvironments. Cluster 3, characterized by the highest βAMRGs scores, displayed the best prognosis, reinforcing β-alanine's significant contribution to HCC pathophysiology. Notably, immune microenvironment, metabolism, and cell death modes significantly varied among the β-alanine subtypes. We developed and validated a novel prognostic panel based on βAMRGs and constructed a nomogram incorporating risk degree and clinicopathological characteristics. Among the model genes, EHHADH has been identified as a protective protein in HCC. Its expression was notably downregulated in tumors and exhibited a close correlation with factors such as tumor staging, grading, and prognosis. Immunohistochemical experiments, conducted using HCC tissue microarrays, substantiated the validation of its expression levels. In conclusion, this study uncovers β-alanine's significant role in HCC for the first time, suggesting new research targets and directions for diagnosis and treatment.

VHL-dependence of EHHADH Expression in a Human Renal Cell Carcinoma Cell Line

The von Hippel-Lindau tumor suppressor gene (VHL) is mutated in up to 90% of clear cell renal cell carcinoma (ccRCC) cases, thus playing a key role in ccRCC pathogenesis. ccRCC can be classified as a metabolic disease in which alterations in fatty acid metabolism facilitate cancer cell proliferation. Enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase (EHHADH) is an enzyme involved in peroxisomal fatty acid degradation. It is primarily expressed in renal proximal tubule cells, presumably the origin of ccRCC. Although EHHADH is still a relatively unexplored gene, it is known to be differentially expressed in several tumors. In this study, analysis of several databases revealed that EHHADH expression is downregulated in ccRCC samples compared to healthy kidney samples. Moreover, cell culture experiments were performed to investigate the relationship between EHHADH and VHL at the gene and protein level. qPCR and Western blot analyses using the human ccRCC cell line RCC4 revealed that EHHADH is expressed in a VHL-dependent manner. RCC4 cells reconstituted with VHL show significantly higher EHHADH mRNA and protein levels than VHL-deficient RCC4 control cells. These results indicate that the downregulation of EHHADH in ccRCC reported may be due to the loss of VHL function. This study is the first to molecularly characterize EHHADH, a key enzyme in peroxisomal ß-oxidation, in relation to VHL, suggesting a potential pathogenic interaction that is worthy of further investigation.

Prediction of Tumor Microenvironment Characteristics and Treatment Response in Lung Squamous Cell Carcinoma by Pseudogene OR7E47P-related Immune Genes

OBJECTIVE

Pseudogenes are initially regarded as nonfunctional genomic sequences, but some pseudogenes regulate tumor initiation and progression by interacting with other genes to modulate their transcriptional activities. Olfactory receptor family 7 subfamily E member 47 pseudogene (OR7E47P) is expressed broadly in lung tissues and has been identified as a positive regulator in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD). This study aimed to elucidate the correlation between OR7E47P and tumor immunity in lung squamous cell carcinoma (LUSC).

METHODS

Clinical and molecular information from The Cancer Genome Atlas (TCGA) LUSC cohort was used to identify OR7E47P-related immune genes (ORIGs) by weighted gene correlation network analysis (WGCNA). Based on the ORIGs, 2 OR7E47P clusters were identified using non-negative matrix factorization (NMF) clustering, and the stability of the clustering was tested by an extreme gradient boosting classifier (XGBoost). LASSO-Cox and stepwise regressions were applied to further select prognostic ORIGs and to construct a predictive model (ORPScore) for immunotherapy. The Botling cohorts and 8 immunotherapy cohorts (the Samstein, Braun, Jung, Gide, IMvigor210, Lauss, Van Allen, and Cho cohorts) were included as independent validation cohorts.

RESULTS

OR7E47P expression was positively correlated with immune cell infiltration and enrichment of immune-related pathways in LUSC. A total of 57 ORIGs were identified to classify the patients into 2 OR7E47P clusters (Cluster 1 and Cluster 2) with distinct immune, mutation, and stromal programs. Compared to Cluster 1, Cluster 2 had more infiltration by immune and stromal cells, lower mutation rates of driver genes, and higher expression of immune-related proteins. The clustering performed well in the internal and 5 external validation cohorts. Based on the 7 ORIGs (HOPX, STX2, WFS, DUSP22, SLFN13, GGCT, and CCSER2), the ORPScore was constructed to predict the prognosis and the treatment response. In addition, the ORPScore was a better prognostic factor and correlated positively with the immunotherapeutic response in cancer patients. The area under the curve values ranged from 0.584 to 0.805 in the 6 independent immunotherapy cohorts.

CONCLUSION

Our study suggests a significant correlation between OR7E47P and TME modulation in LUSC. ORIGs can be applied to molecularly stratify patients, and the ORPScore may serve as a biomarker for clinical decision-making regarding individualized prognostication and immunotherapy.

The Physiological and Pathological Role of Acyl-CoA Oxidation

Fatty acid metabolism, including β-oxidation (βOX), plays an important role in human physiology and pathology. βOX is an essential process in the energy metabolism of most human cells. Moreover, βOX is also the source of acetyl-CoA, the substrate for (a) ketone bodies synthesis, (b) cholesterol synthesis, (c) phase II detoxication, (d) protein acetylation, and (d) the synthesis of many other compounds, including N-acetylglutamate-an important regulator of urea synthesis. This review describes the current knowledge on the importance of the mitochondrial and peroxisomal βOX in various organs, including the liver, heart, kidney, lung, gastrointestinal tract, peripheral white blood cells, and other cells. In addition, the diseases associated with a disturbance of fatty acid oxidation (FAO) in the liver, heart, kidney, lung, alimentary tract, and other organs or cells are presented. Special attention was paid to abnormalities of FAO in cancer cells and the diseases caused by mutations in gene-encoding enzymes involved in FAO. Finally, issues related to α- and ω- fatty acid oxidation are discussed.

Development and validation of a mitochondrial energy metabolism-related risk model in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers and ranks third inmortality. Mitochondria are the energy manufacturers of cells. Disruption of mitochondrial energy metabolism pathways is strongly correlated with the onset and progression of HCC. Aberrant genes in mitochondrial energy metabolism pathways may represent a unique diagnostic and therapeutic targets that act as indicators for HCC.

METHODS

Gene expression data from 374 HCC patients and 50 controls were acquired from TCGA database. A total of 188 mitochondrial energy metabolism-related genes (MMRGs) were obtained from KEGG PATHWAY database. A total of 368 patients with survival data were randomly split into training and validation groups in a 7: 3 ratio. Prognosis-related MMRGs were selected by univariate Cox and LASSO analyses. Kaplan-Meier and ROC curves were employed to analyze the model precision, whereas the validation set was used for model verification. Furthermore, clinical examinations, immune infiltration analysis, GSVA, and immunotherapy analysis were conducted in the high- and low-risk groups. Finally, the risk model was combined with the clinical variables of HCC patients to perform univariate and multivariate Cox regression analyses to obtain independent risk indicators and draw a nomogram. Therefore, we evaluated the accuracy of the predictions using calibration curves.

RESULTS

A total of 6032 differentially expressed genes (DEGs) were detected in the HCC and control samples. After overlapping DEGs with 188 MMRGs, 42 mitochondrial energy metabolism-related DEGs (DEMMRGs) were identified. A 17 specific genes-based risk score model of HCC was created, which revealed effectiveness in each TCGA training and validation dataset. Moreover, patients categorized by risk scores exhibited distinct immune infiltration status, immunotherapy responsiveness, and functional properties. Finally, univariate and multivariate Cox regression analyses revealed that risk score and stage T were independent predictive variables. Based on the T stage and risk score, a nomogram for estimating the survival of HCC patients was created. The calibration curves demonstrated that the prediction model had a high level of accuracy.

CONCLUSIONS

Our study constructed a mitochondrial energy metabolism-related risk model, that may be utilized to anticipate HCC prognosis and represent the immunological microenvironment of HCC.