Identifying SLC27A5 as a potential prognostic marker of hepatocellular carcinoma by weighted gene co-expression network analysis and in vitro assays

DNA methylation regulator-based molecular subtyping and tumor microenvironment characterization in hepatocellular carcinoma

Backgroud

Although recent studies have reported the regulation of the immune response in hepatocellular carcinoma (HCC) through DNA methylation, the comprehensive impact methylation modifications on tumor microenvironment characteristics and immunotherapy efficacy has not been fully elucidated.

Methods

In this research, we conducted a comprehensive assessment of the patterns of DNA methylation regulators and the profiles of the tumor microenvironment (TME) in HCC, focusing on 21 specific DNA methylation regulators. We subsequently developed a unique scoring system, a DNA methylation score (DMscore), to assess the individual DNA methylation modifications among the three distinct methylation patterns for differentially expressed genes (DEGs).

Results

Three distinct methylation modification patterns were identified with distinct TME infiltration characteristics. We demonstrated that the DMscore could predict patient subtype, TME infiltration, and patient prognosis. A low DMscore, characterized by an elevated tumor mutation burden (TMB), hepatitis B virus (HBV)/hepatitis C virus (HCV) infection, and immune activation, indicates an inflamed tumor microenvironment phenotype with a 5-year survival rate of 7.8%. Moreover, a low DMscore appeared to increase the efficacy of immunotherapy in the anti-CTLA-4/PD-1/PD-L1 cohort.

Conclusions

In brief, this research has enhanced our understanding of the correlation between modifications in DNA methylation patterns and the profile of the tumor microenvironment in individuals diagnosed with HCC. The DMscore may serve as an alternative biomarker for survival and efficacy of immunotherapy in patients with HCC.

Metabolic Enzyme SLC27A5 Regulates PIP4K2A pre-mRNA Splicing as a Noncanonical Mechanism to Suppress Hepatocellular Carcinoma Metastasis

Solute carrier family 27 member 5, a key enzyme in fatty acid transport and bile acid metabolism in the liver, is frequently expressed in low quantities in patients with hepatocellular carcinoma, resulting in poor prognosis. However, it is unclear whether SLC27A5 plays non-canonical functions and regulates HCC progression. Here, an unexpected non-canonical role of SLC27A5 is reported: regulating the alternative splicing of mRNA to inhibit the metastasis of HCC independently of its metabolic enzyme activity. Mechanistically, SLC27A5 interacts with IGF2BP3 to prevent its translocation into the nucleus, thereby inhibiting its binding to target mRNA and modulating PIP4K2A pre-mRNA splicing. Loss of SLC27A5 results in elevated levels of the PIP4K2A-S isoform, thus positively regulating phosphoinositide 3-kinase signaling via enhanced p85 stability in HCC. SLC27A5 restoration by AAV-Slc27a5 or IGF2BP3 RNA decoy oligonucleotides exerts an inhibitory effect on HCC metastasis with reduced expression of the PIP4K2A-S isoform. Therefore, PIP4K2A-S may be a novel target for treating HCC with SLC27A5 deficiency.

SLC27A5 promotes sorafenib-induced ferroptosis in hepatocellular carcinoma by downregulating glutathione reductase

Sorafenib, a first-line drug for advanced hepatocellular carcinoma (HCC), shows a favorable anti-tumor effect while resistance is a barrier impeding patients from benefiting from it. Thus, more efforts are needed to lift this restriction. Herein, we first find that solute carrier family 27 member 5 (SLC27A5/FATP5), an enzyme involved in the metabolism of fatty acid and bile acid, is downregulated in sorafenib-resistant HCC. SLC27A5 deficiency facilitates the resistance towards sorafenib in HCC cells, which is mediated by suppressing ferroptosis. Further mechanism studies reveal that the loss of SLC27A5 enhances the glutathione reductase (GSR) expression in a nuclear factor erythroid 2-related factor 2 (NRF2)-dependent manner, which maintains glutathione (GSH) homeostasis and renders insensitive to sorafenib-induced ferroptosis. Notably, SLC27A5 negatively correlates with GSR, and genetic or pharmacological inhibition of GSR strengthens the efficacy of sorafenib through GSH depletion and the accumulation of lipid peroxide products in SLC27A5-knockout and sorafenib-resistant HCC cells. Based on our results, the combination of sorafenib and carmustine (BCNU), a selective inhibitor of GSR, remarkably hamper tumor growth by enhancing ferroptotic cell death in vivo. In conclusion, we describe that SLC27A5 serves as a suppressor in sorafenib resistance and promotes sorafenib-triggered ferroptosis via restraining the NRF2/GSR pathway in HCC, providing a potential therapeutic strategy for overcoming sorafenib resistance.

Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma

Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes. We screened differentially expressed proteins between tumorous and adjacent nontumorous tissues of hepatitis B virus (HBV)-related HCC patients using a Nanoscale Liquid Chromatography–Tandem Mass Spectrometry platform and combined it with transcriptomic data of lipid-metabolism-related genes from the GEO and HPA databases to identify dysregulated genes that may be involved in lipid metabolic processes. The potential clinical values of these genes were explored by bioinformatics online analysis tools (GEPIA, cBioPortal, SurvivalMeth, and TIMER). The expression levels of the secreted protein (angiopoietin-like protein 6, ANGPTL6) in serum were analyzed by ELISA. The ability of serum ANGPTL6 to diagnose early HCC was assessed by ROC curves. The results showed that serum ANGPTL6 could effectively differentiate between HBV-related early HCC patients with normal serum alpha-fetoprotein (AFP) levels and the noncancer group (healthy participants and chronic hepatitis B patients) (AUC = 0.717, 95% CI: from 0.614 to 0.805). Serum ANGPTL6 can be used as a potential second-line biomarker to supplement serum AFP in the early diagnosis of HBV-related HCC.

Machine learning algorithm and deep neural networks identified a novel subtype in hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. Due to the lack of specific characteristics in the early stage of the disease, patients are usually diagnosed in the advanced stage of disease progression. OBJECTIVE: This study used machine learning algorithms to identify key genes in the progression of hepatocellular carcinoma and constructed a prediction model to predict the survival risk of HCC patients. METHODS: The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differential expression analysis and COX proportional-hazards model participated in the identification of survival-related genes. K-Means, Random forests, and LASSO regression are involved in identifying novel subtypes of HCC and screening key genes. The prediction model was constructed by deep neural networks (DNN), and Gene Set Enrichment Analysis (GSEA) reveals the metabolic pathways where key genes are located. RESULTS: Two subtypes were identified with significantly different survival rates (p< 0.0001, AUC = 0.720) and 17 key genes associated with the subtypes. The accuracy rate of the deep neural network prediction model is greater than 93.3%. The GSEA analysis found that the survival-related genes were significantly enriched in hallmark gene sets in the MSigDB database. CONCLUSIONS: In this study, we used machine learning algorithms to screen out 17 genes related to the survival risk of HCC patients, and trained a DNN model based on them to predict the survival risk of HCC patients. The genes that make up the model are all key genes that affect the formation and development of cancer.

Cuproptosis-Related Risk Score Predicts Prognosis and Characterizes the Tumor Microenvironment in Hepatocellular Carcinoma

Aims

Cuproptosis is a recently identified form of programmed cell death; however, its role in hepatocellular carcinoma (HCC) remains unclear.

Methods

A set of bioinformatic tools was integrated to analyze the expression and prognostic significance of ferredoxin 1 (FDX1), the key regulator of cuproptosis. A cuproptosis-related risk score (CRRS) was developed via correlation analyses, least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox regression. The metabolic features, mutation signatures, and immune profile of CRRS-classified HCC patients were investigated, and the role of CRRS in therapy guidance was analyzed.

Results

FDX1 was significantly downregulated in HCC, and its high expression was associated with longer survival time. HCC patients in the high-CRRS group showed a significantly lower overall survival (OS) and enriched in cancer-related pathways. Mutation analyses revealed that the high-CRRS HCC patients had a high mutational frequency of some tumor suppressors such as tumor protein P53 (TP53) and Breast-cancer susceptibility gene 1 (BRCA1)-associated protein 1 (BAP1) and a low frequency of catenin beta 1 (CTNNB1). Besides, HCC patients with high CRRS showed an increase of protumor immune infiltrates and a high expression of immune checkpoints. Moreover, the area under the curve (AUC) values of CRRS in predicting the efficiency of sorafenib and the non-responsiveness to transcatheter arterial chemoembolization (TACE) in HCC patients reached 0.877 and 0.764, respectively.

Significance

The cuproptosis-related signature is helpful in prognostic prediction and in guiding treatment for HCC patients.

Solute Carrier Family 27 Member 6 (SLC27A6) Possibly Promotes the Proliferation of Papillary Thyroid Cancer by Regulating c-MYC

To investigate the expression and mechanism of LSC27A6 in papillary thyroid cancer (PTC). We analyzed the differential expression of SLC27A6 in PTC tissues and normal tissues based on the TCGA database and validated it using immunohistochemistry. Wilcoxon rank sum, chi-square test, or Fisher exact exam were used to analyze the relationship between the expression of SLC27A6 and clinicopathological information. Samples were divided into two groups according to whether BRAF was mutated or not, and Wilcoxon rank sum was used to determine whether the expression of SLC27A6 was related to BRAF mutation. The effects of SLC27A6 on the proliferation, migration, and apoptosis of PTC cells were detected by cell counting kit-8 (CCK8), colony formation assay, transwell assay, and flow cytometry. Spearman correlation analysis was used to evaluate the relationship between SLC27A6 and c-MYC. Protein expression was detected by Western blot. The expression of SLC27A6 was higher in PTC and positively correlated with N stage. SLC27A6 expression was higher in samples with BRAF mutations. Down-regulation of SLC27A6 inhibited cell proliferation, migration, and invasion and induced apoptosis. Spearman correlation analysis showed that SLC27A6 was positively correlated with c-MYC. Knockdown of SLC27A6 inhibited c-MYC expression. Our results suggest that SLC27A6 is overexpressed in PTC tissues and affects the progression of PTC by regulating c-MYC.

A robust gene expression signature for NASH in liver expression data

Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.

The transcriptome of early GGT/KRT19-positive hepatocellular carcinoma reveals a downregulated gene expression profile associated with fatty acid metabolism

Hepatocellular carcinoma expressing hepatobiliary progenitor markers, is considered of poor prognosis. By using a hepatocarcinogenesis model, laser capture microdissection, and RNA-Sequencing analysis, we identified an expression profile in GGT/KRT19-positive experimental tumors; 438 differentially expressed genes were found in early and late nodules along with increased collagen deposition. Dysregulated genes were involved in Fatty Acid Metabolism, RXR function, and Hepatic Stellate Cells Activation. Downregulation of Slc27a5, Acsl1, and Cyp2e1, demonstrated that Retinoid X Receptor α (RXRα) function is compromised in GGT/KRT19-positive nodules. Since RXRα controls NRF2 pathway activation, we determined the expression of NRF2 targeted genes; Akr1b8, Akr7a3, Gstp1, Abcc3, Ptgr1, and Txnrd1 were upregulated, indicating NRF2 pathway activation. A comparative analysis in human HCC showed that SLC27A5, ACSL1, CYP2E1, and RXRα gene expression is mutually exclusive with KRT19 gene expression. Our results indicate that the downregulation of Slc27a5, Acsl1, Rxrα, and Cyp2e1 genes is an early event within GGT/KRT19-positive HCC.