Network-based analysis of candidate oncogenes and pathways in hepatocellular carcinoma

Overexpression of matrix metalloproteinase-12 (MMP-12) correlates with poor prognosis of hepatocellular carcinoma

To develop a model for predicting the overall survival (OS) of hepatocellularcarcinoma (HCC) patients after transarterial chemoembolization (TACE) on the basis of multisequence MRI radiomic features and clinical variables. The DCE-MRI and clinical data of 116HCC patients treated with TACE for the first time were retrospectively analyzed. The included patients were randomly divided into training and validation cohorts at a ratio of 7:3. Univariate and multivariate Cox proportional hazards regression models were used to identify independent risk factors that affect the OS of patients with HCC after TACE. Radiomic features were extracted from the sequences of FS-T2W images and arterial-phase (A) and portal venous-phase (P) axial DCE-MR images. The LASSO method was used to select the best radiomic features. Logistic regression was used to establish a radiomic model of each sequence, a joint model of MRI features (M model) combined the radiomic features of all the sequences, and a radiomic-clinical model (M-C model) that integrated the radiomic signatures and clinically independent predictors. The diagnostic performance of each model was evaluated as the area under the receiver operating characteristic (ROC) curve (AUC). The Child-Turcotte-Pugh (CTP) score and neutrophil-to-lymphocyte ratio (NLR) -platelet-to-lymphocyte ratio (PLR) were found to be independent risk factors that affect the OS of patients with HCC treated with TACE. The AUCs of the FS-T2WI, A, P, M, and M-C models for predicting the OS of HCC patients after TACE treatment were 0.779, 0.803, 0.745, 0.858 and 0.893, respectively, in the training group and 0.635, 0.651, 0.644, 0.778 and 0.803, respectively, in the validation group. The M-C model had the best predictive performance. Multiparameter MRI-based radiomic features may be helpful for predicting OS after TACE treatment in HCC patients. The inclusion of clinical indicators such as inflammation scores can improve the predictive performance.

Activation of STAT3 Signal Pathway Correlates with Twist and E-Cadherin Expression in Hepatocellular Carcinoma and Their Clinical Significance

Background: Natural killer (NK) cells are a type of innate immune cell that recognize and eliminate tumor cells and infected cells, without prior sensitization or activation. Herein, we aimed to construct a predictive model based on NK cell-related genes for hepatocellular carcinoma (HCC) patients and assess the feasibility of utilizing this model for prognosis prediction. Methods: Single-cell RNA-seq data were obtained from the Gene Expression Omnibus (GEO) database to identify marker genes of NK cells. Univariate Cox and lasso regression were performed to further establish a signature in the TCGA dataset. Subsequently, qPCR and immunohistochemistry (IHC) staining were employed to validate the expression levels of prognosis signature genes in HCC. The effectiveness of the model was further validated using two external cohorts from the GEO and ICGC datasets. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, and biological function were compared for different genetic subtypes and risk groups. Finally, molecular docking was performed to evaluate the binding affinity between the hub gene and chemotherapeutic drugs. Results: A total of 161 HCC-related NK cell marker genes (NKMGs) were identified, 28 of which were significantly associated with overall survival in HCC patients. Based on differences in gene expression characteristics, HCC patients were classified into three subtypes. Ten prognosis genes (KLRB1, CD7, LDB2, FCER1G, PFN1, FYN, ACTG1, PABPC1, CALM1, and RPS8) were screened to develop a prognosis model. The model not only demonstrated excellent predictive performance on the training dataset, but also were successfully validated on two independent external datasets. The risk scores derived from the model were shown to be an independent prognosis factor for HCC and were correlated with pathological severity. Moreover, qPCR and IHC staining confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis. Finally, molecular docking revealed favorable binding energies between the hub gene ACTG1 and chemotherapeutic drugs. Conclusion: In this study, we developed a model for predicting the prognosis of HCC based on NK cells. The utilization of NKMGs as innovative biomarkers showed promise in the prognosis assessment of HCC.

Hepatocellular carcinoma (HCC) is a liver disease with a complex underlying mechanism, and patients with HCC have low survival rates. Iron metabolism plays a crucial role in the pathogenesis of HCC; however, the prognostic value of iron metabolism-related and methylated genes for HCC needs to be further explored. In the present study, we identified differentially expressed genes (DEGs) that play a role in iron metabolism and DNA methylation in HCC from The Cancer Genome Atlas. Four of these DEGs, whose expression levels are correlated with HCC prognosis, namely, RRM2, FTCD, CYP2C9, and ATP6V1C1, were further used to construct a prognostic model for HCC, wherein the risk score was calculated using the gene expression of the four DEGs. This could be used to predict the overall survival of HCC patients for 1, 3, and 5 years. Results of a multivariate Cox regression analysis further indicated that the risk score was an independent variable correlated with the prognosis of HCC patients. The identified gene signature was further validated using an independent cohort of HCC patients from the International Cancer Genome Consortium. Weighted gene co-expression network analysis and gene set enrichment analysis were performed to identify potential regulatory mechanisms of the gene signature in HCC. Taken together, we identified key prognostic factors of iron metabolism-related and methylated genes for HCC, providing a potential treatment strategy for HCC.

Aims: We aim to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) and identify key genes as biomarkers for the prognosis of HCC. Materials & methods: Differentially expressed genes between HCC tissues and normal tissues were identified via the Gene Expression Omnibus tool. The top ten hub genes screened by the degree of the protein nodes in the protein-protein interactionnetwork also showed significant associations with overall survival in HCC patients. Results: A prognostic model containing a five-gene signature was constructed to predict the prognosis of HCC via multivariate Cox regression analysis. Conclusion: This study identified a novel five-gene signature (CDK1, CCNB1, CCNB2, BUB1and KIF11) as a significant independent prognostic factor.

BACKGROUND Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer. The primary treatment strategies for HCC currently include liver transplantation and surgical resection. However, these methods often yield unsatisfactory outcomes, leading to a poor prognosis for many patients. This underscores the urgent need to identify and evaluate novel therapeutic targets that can improve the prognosis and survival rate of HCC patients. AIM To construct a radiomics model that can accurately predict the EZH2 expression in HCC. METHODS Gene expression, clinical parameters, HCC-related radiomics, and fibroblast-related genes were acquired from public databases. A gene model was developed, and its clinical efficacy was assessed statistically. Drug sensitivity analysis was conducted with identified hub genes. Radiomics features were extracted and machine learning algorithms were employed to generate a radiomics model related to the hub genes. A nomogram was used to illustrate the prognostic significance of the computed Radscore and the hub genes in the context of HCC patient outcomes. RESULTS EZH2 and NRAS were independent predictors for prognosis of HCC and were utilized to construct a predictive gene model. This model demonstrated robust performance in diagnosing HCC and predicted an unfavorable prognosis. A negative correlation was observed between EZH2 expression and drug sensitivity. Elevated EZH2 expression was linked to poorer prognosis, and its diagnostic value in HCC surpassed that of the risk model. A radiomics model, developed using a logistic algorithm, also showed superior efficiency in predicting EZH2 expression. The Radscore was higher in the group with high EZH2 expression. A nomogram was constructed to visually demonstrate the significant roles of the radiomics model and EZH2 expression in predicting the overall survival of HCC patients. CONCLUSION EZH2 plays significant roles in diagnosing HCC and therapeutic efficacy. A radiomics model, developed using a logistic algorithm, efficiently predicted EZH2 expression and exhibited strong correlation with HCC prognosis.

Simple SummaryLiquid biopsy for cell-free DNA (cfDNA) is a non-invasive technique to characterize the genetic profile of a tumor. Despite being a valuable tool, there is no mutational profile of cfDNA from hepatocellular carcinoma (HCC) in patients from Thailand, where HCC is prevalent. The present study aimed to demonstrate the utility of using whole-exome sequencing of cfDNA to define the somatic mutation profiles of HCC in Thai patients who underwent nonoperative therapies. The level of cfDNA was higher in HCC patients than in chronic hepatitis patients. Single nucleotide variations were present in somatic genes in cfDNA, including in ZNF814, HRNR, ZNF492, ADAMTS12, FLG, OBSCN, TP53, and TTN. The co-occurrence of HRNR and TTN mutations in cfDNA was associated with shorter overall survival. These findings indicate that the mutational profiles of cfDNA reflected those of HCC tissue, and cfDNA could serve as a useful biomarker for diagnosis and prognosis in HCC patients.Cell-free DNA (cfDNA) has been used as a non-invasive biomarker for detecting cancer-specific mutations. However, the mutational profile of cfDNA in Thai patients with hepatocellular carcinoma (HCC) has not been investigated. Here, we demonstrated the utility of using whole-exome sequencing (WES) of cfDNA to define the somatic mutation profiles of HCC in Thai patients. The comprehensive profile of cfDNA was determined with WES to identify variants in matched cfDNA and germline DNA from 30 HCC patients in Thailand who underwent nonoperative therapies. The level of cfDNA was higher in HCC patients compared with chronic hepatitis patients (p-value < 0.001). Single nucleotide variants were present in somatic genes in cfDNA, including in ZNF814 (27%), HRNR (20%), ZNF492 (20%), ADAMTS12 (17%), FLG (17%), OBSCN (17%), TP53 (17%), and TTN (17%). These same mutations were matched to HCC mutation data from The Cancer Genome Atlas (TCGA) and a previous Thai HCC study. The co-occurrence of HRNR and TTN mutations in cfDNA was associated with shorter overall survival in HCC patients (hazard ratio = 1.60, p-value = 0.0196). These findings indicate that the mutational profile of cfDNA accurately reflected that of HCC tissue and suggest that cfDNA could serve as a useful biomarker for diagnosis and prognosis in Thai HCC patients. In addition, we demonstrated the use of the pocket-sized sequencer of Oxford Nanopore Technology to detect copy-number variants in HCC tissues that could be applied for onsite clinical detection/monitoring of HCC.

Elongation factor Tu GTP binding domain containing 2 (EFTUD2), a spliceosomal GTPase, plays a pivotal role in multiple organ development and innate immune. It has been reported that EFTUD2 is a new host factor with activity against HCV infection. However, the role of EFTUD2 in solid tumors, including hepatocellular carcinoma (HCC), remains unexplored. In this study, we investigated the molecular function of EFTUD2 in HCC. Data from The Cancer Genome Atlas (TCGA) indicated an upregulation of EFTUD2 in HCC tissues compared to that in nontumor liver tissues. Immunohistochemical analysis performed on two independent HCC cohorts confirmed the upregulation of EFTUD2 in HCC tissues and further suggested that a high level of EFTUD2 expression predicted shorter overall and recurrence-free survival in HCC patients. Functional studies suggested that siRNA interference with EFTUD2 expression significantly suppressed cell viability, blocked cell cycle progression, facilitated tumor cell apoptosis, and inhibited metastasis, while the enhancement of EFTUD2 expression promoted the proliferation and migration of HCC cells both in vitro and in vivo. Surprisingly, we also found that the stable knockdown of EFTUD2 expression via lentivirus infection was lethal for HCC cells. This finding suggested that EFTUD2 was essential for maintaining the survival of HCC cells. Mechanistically, RNA sequencing and gene set enrichment analysis (GSEA) suggested that the gene sets of epithelial–mesenchymal transition (EMT) and the JAK/STAT3 pathway were enriched in EFTUD2-overexpressing cells. Further verification indicated that EFTUD2-overexpressing cells exhibited an EMT-like phenotype and had enhanced STAT3 activation, while the STAT3 inhibitor S3I-201 partially blocked these pro-malignant effects of EFTUD2 overexpression. In summary, we report EFTUD2 as a novel oncogene that helps to maintain the survival of HCC cells and promotes HCC progression through the activation of STAT3. The high level of expression of EFTUD2 in HCC tissues indicates shorter overall and recurrence-free survival in HCC patients.

Monocarboxylate transporter 4 (MCT4) is a critical component in the glycolytic metabolism of cancer cells, and is also important for malignant behavior. We investigated the expression profile of MCT4, its prognostic value in hepatocellular carcinoma (HCC) patients, its role in HCC cell proliferation and metastasis, and associated initial molecular mechanism. MCT4 expression was examined through immunohistochemical staining of pathological specimens from 318 HCC patients who had undergone hepatectomy. The HCC cell lines were used to validate the relationship between MCT4 expression and cell proliferation, migration, and invasion. The results show that high MCT4 expression is indicative of elevated alpha fetoprotein levels and larger tumor size, which leads to poorer disease-free survival (DFS) and overall survival (OS). Multivariate regression analysis shows that MCT4 expression is an independent prognostic factor for DFS and OS in HCC patients. In 91 recurrent HCC patients who underwent transarterial chemoembolization (TACE) treatment, low MCT4 expression predicted an effective treatment response and improved OS. Furthermore, in cell line experiments with MCT4 siRNA, cancer cell proliferation, migration, and invasion were closely correlated with the MCT4 expression. Knockdown of MCT4 was associated with down-regulation of phosphorylated AKT and HIF-1α. MCT4 expression can predict survival and TACE treatment response for HCC patients. Furthermore, MCT4 plays an important role in HCC cell proliferation, migration, and invasion. The inhibition of MCT4 can induce inactivation of HIF-1α and inhibit phosphorylation of AKT. MCT4 may be a potential therapeutic target for the treatment of HCC.

BackgroundThe benefit of statins in overall survival of hepatocellular carcinoma (HCC) patients after curative liver resection has been controversial. Some retrospective studies identified perioperative use of statins was associated with...

Aim: The reprogramming of lipid metabolism can markedly enhance the nutritional adaptability of tumor cells to the glucose-deficient and hypoxic tumor microenvironment, which holds profound significance for the development and metastasis of liver cancer. Nevertheless, the alterations of lipid metabolism under stress conditions and the specific mechanisms remain ambiguous. The current study aimed to explore the molecular interaction between endoplasmic reticulum (ER) stress and lipid metabolism in hepatocellular carcinoma (HCC) using bioinformatics analysis, and further verify the role of core hub genes and offer potential targets for diagnosing and treating HCC. Methods: Differentially expressed lipid-related genes (DLRGs) were identified via cross-crossing differentially expressed genes (DEGs) in the TCGA-LIHC program and lipid metabolism-related genes in the Genecards database. Identification of hub genes was achieved by constructing a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Disease correlation analysis was performed in the Comparison of Toxicology Database, receiver operating characteristic (ROC) curve and Kaplan-Meier curve analyses were performed for the hub genes, and the CIBERSORT algorithm was employed to assess immune infiltration. The role of acetyl-CoA carboxylase 1 (ACACA) in HCC was evaluated by Western blotting, polymerase chain reaction, immunohistochemistry, and CCK-8 assay. Results: In total, 131 DLRGs were identified, comprising 70 upregulated and 61 downregulated. PPI analysis identified 20 hub DLRGs, while ROC curve analysis and Kaplan-Meier analysis further revealed that ACACA, LCAT, APOC3, LPA and PON1 may hold diagnostic and prognostic value for HCC patients. More importantly, ACACA overexpression was related to unfavorable overall survival (OS) and adverse pathological characteristics in HCC patients. In addition, both free fatty acid (FFA) and tunicamycin (TM) could activate ER stress and enhance the expression of ACACA in HCC. Interestingly, inhibition of ER stress or fatty acid synthesis using 4-phenylbutyric acid (4-PBA) or fenofibrate significantly reduced the expression of ACACA, and fenofibrate inhibits HCC cell proliferation. Conclusion: The study identifies a novel core lipid metabolism-related gene called ACACA, which has prognostic and therapeutic potential for HCC. We also provide a deep understanding of lipid metabolism correlated with ER stress in the progression of HCC, offering new opportunities for the identification of biological targets and the development of drugs and treatments for HCC patients.

Hepatocellular carcinoma (HCC) is a primary malignant tumor of the liver, and pyroptosis has been identified as a novel cellular program that plays a role in numerous diseases including cancer. However, the functional role of pyroptosis in HCC remains unclear. The purpose of this study is to explore the relationship between the two found hub genes and provide targets for clinical treatment. The Cancer Genome Atlas (TCGA) database was used to collect the gene data and clinically-related information of patients with HCC. After the differentially expressed genes (DEGs) were identified, they were intersected with the genes related to pyroptosis, and a risk prediction model was established to predict the overall survival (OS). Subsequently, drug sensitivity analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) was used to analyze the biological characteristics of the DEGs. Different immune cell infiltration and related pathways were analyzed, and hub genes were identified by protein-protein interaction (PPI). Finally, the expression of hub genes was verified by real-time quantitative PCR (qRT-PCR) and immunohistochemistry. We conducted a comprehensive bioinformatics analysis to investigate the molecular mechanisms of pyroptosis in hepatocellular carcinoma (HCC). A total of 8,958 differentially expressed genes were identified, and 37 differentially expressed genes were associated with pyroptosis through intersection. Moreover, we developed an OS model with excellent predictive ability and discovered the differences in biological function, drug sensitivity, and immune microenvironment between high-risk and low-risk groups. Through enrichment analysis, we found that the differentially expressed genes are related to various biological processes. Then, 10 hub genes were identified from protein-protein interaction networks. Finally, midkine (MDK) was screened from the 10 hub genes and further verified by PCR and immunohistochemistry, which revealed its high expression in HCC. We have developed a reliable and consistent predictive model based on the identification of potential hub genes, which can be used to accurately forecast the prognosis of patients, thus providing direction for further clinical research and treatment.

BackgroundIncreasing evidence shows that liver-specific long non-coding RNAs (lncRNAs) play important roles in the development of hepatocellular carcinoma (HCC). We identified a novel liver-specific lncRNA, FAM99A, and examined its clinical significance and biological functions in HCC.MethodsThe expression level and clinical value of FAM99A in HCC were examined using The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases, and were further verified using quantitative real-time polymerase chain reaction (qRT–PCR) in our HCC cohort. Univariate and multivariate Cox proportional hazards regression models were also applied to identify independent prognostic indicators for HCC patients. Cell counting kit-8, colony formation, and Transwell assays were performed to evaluate the effects of FAM99A on the proliferation, migration, and invasion abilities of HCC cells in vitro. A subcutaneous xenograft tumor model was implemented to determine the effect of FAM99A on the tumor growth of HCC cells in vivo. RNA pull-down and mass spectrometry assays were performed to reveal the potential molecular mechanisms of FAM99A in HCC.ResultsThe three public online databases and qRT–PCR data showed that FAM99A was frequently downregulated in HCC tissues and inversely correlated with microvascular invasion and advanced histological grade of HCC patients. Kaplan–Meier survival analysis indicated that decreased FAM99A was significantly associated with poor overall survival of HCC patients based on TCGA database (P = 0.040), ICGC data portal (P < 0.001), and our HCC cohort (P = 0.010). A multivariate Cox proportional hazards regression model based on our HCC cohort suggested that FAM99A was an independent prognostic factor of overall survival for HCC patients (hazard ratio: 0.425, P = 0.039). Upregulation of FAM99A suppressed the proliferation, colony formation, migration, and invasion capacities of HCC cells in vitro, and knockdown of FAM99A had the opposite effects. A subcutaneous xenograft tumor model demonstrated that overexpression of FAM99A significantly inhibited the tumor growth of HCC cells in vivo. Seven tumor-related proteins (PCBP1, SRSF5, SRSF6, YBX1, IGF2BP2, HNRNPK, and HNRNPL) were recognized as possible FAM99A-binding proteins by the RNA pull-down and mass spectrometry assays.ConclusionOur results suggest that FAM99A exerts cancer-inhibiting effects on HCC progression, and it may be a promising prognostic indicator for HCC patients.

BackgroundTransarterial chemoembolization(TACE) is the suggested treatment for hepatocellular carcinoma (HCC) not amenable to curative treatments. We investigated the role of sarcopenia on overall survival in HCC patients receiving TACE and proposed a new prognostic scoring system incorporating sarcopenia.Materials and methodsWe retrospectively analyzed 260 HCC patients who received TACE between 2010 and 2015. Total psoas muscle was measured on a cross-sectional CT image before the first TACE session. Sarcopenia was defined by the pre-determined sex-specific cutoff value. We assessed the impact of sarcopenia and other biochemical factors on the overall survival and compared the new scoring system with other prognostic scoring systems.ResultsOne hundred and thirty patients (50%) were classified as sarcopenia before the first TACE. They were older with a higher male tendency and a significantly lower body mass index (BMI). Cox regression multivariate analysis demonstrated that sarcopenia, multiple tumors, maximal tumor diameter≥ 5cm, major venous thrombosis, sarcopenia, AFP ≥ 200 ng/ml, and albumin<3.5mg/dL were independent poor prognostic factors for overall survival in HCC patients receiving TACE. Our scoring system comprising these factors outperformed other major scoring systems in terms of predicting survival after TACE.ConclusionThe current study demonstrated that sarcopenia was an independent prognostic factor for HCC undergoing TACE therapy. Our newly developed scoring system could effectively predict patient survival after TACE. Physicians could, based on the current score model, carefully select candidate patients for TACE treatment in order to optimize their survival. Further studies are warranted to validate our findings.