Significance In Hepatocellular Carcinoma Research Articles

Identification of metabolism-related long non-coding RNA (lncRNA) signature predicts prognosis and immune infiltrates in hepatocellular carcinoma.

BackgroundCancer-associated metabolic reprogramming promotes cancer cell differentiation, growth, and influences the tumor immune microenvironment (TIME) to promote hepatocellular carcinoma (HCC) progression. However, the clinical significance of metabolism-related lncRNA remains largely unexplored.MethodsBased on The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic long non-coding RNAs (lncRNAs) and construct metabolism-related lncRNA prognostic signature for HCC. Gender, age, grade, stage and TP53 status were used as covariates were used to assess the prognostic capacity of the characteristic lncRNA signature. Subsequently, the molecular and immune characteristics and drug sensitivity in metabolism-related lncRNA signature defined subgroups were analyzed.ResultsWe identified 34 metabolism-related lncRNAs significantly associated with the prognosis of HCC (P<0.05). Subsequently, we constructed a multigene signature based on 9 characteristics prognostic lncRNAs and classified HCC patients into high- and low-risk groups based on cutoff values. We found the lncRNA signature [hazard ratio (HR) =3.55 (2.44–5.15), P<0.001] to be significantly associated with survival. The receiver operating characteristic curve (ROC) curves area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.811, 0.773, and 0.753, respectively. In univariate and multivariate Cox regression analyses, prognostic characteristic lncRNAs were the most crucial prognostic factor besides the stage. The prognostic signature was subsequently validated in the test set. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analyses revealed potential biological features and signaling pathways associated with the prognostic signature. We constructed a nomogram including risk groups and clinical parameters (age, gender, grade, and stage). Calibration plots and decision curve analysis (DCA) showed that our nomogram had a good predictive performance. Finally, we found reduced expression of immune-activated cells in the high-risk group.ConclusionsThe metabolism-related lncRNA signature is a promising biomarker to distinguish the prognosis and an immune characteristic in HCC.

A Predictive Model for Prognosis and Therapeutic Response in Hepatocellular Carcinoma Based on a Panel of Three MED8-Related Immunomodulators.

The current tumor-node-metastasis (TNM) system is limited in predicting the survival and guiding the treatment of hepatocellular carcinoma (HCC) patients since the TNM system only focuses on the anatomical factors, regardless of the intratumoral molecule heterogeneity. Besides, the landscape of intratumoral immune genes has emerged as a prognostic indicator. The mediator complex subunit 8 (MED8) is a major polymerase regulator and has been described as an oncogene in renal cell carcinoma, but its pathophysiological significance of HCC and its contribution to the prognosis of HCC remain unclear. Here, we aimed to discuss the expression profile and clinical correlation of MED8 in HCC and construct a predictive model based on MED8-related immunomodulators as a supplement to the TNM system. According to our analyses, MED8 was overexpressed in HCC tissues and increased expression of MED8 was an indicator of poor outcome in HCC. The knockdown of MED8 weakened the proliferation, colony forming, and migration of HepG2 and Huh7 cells. Subsequently, a predictive model was identified based on a panel of three MED8-related immunomodulators using The Cancer Genome Atlas (TCGA) database and further validated in International Cancer Genome Consortium (ICGC) database. The combination of the predictive model and the TNM system could improve the performance in predicting the survival of HCC patients. High-risk patients had poor overall survival in TCGA and ICGC databases, as well as in subgroup analysis with early clinicopathology classification. It was also found that high-risk patients had a higher probability of recurrence in TCGA cohort. Furthermore, low-risk score indicated a better response to immunotherapy and drug therapy. This predictive model can be served as a supplement to the TNM system and may have implications in prognosis stratification and therapeutic guidance for HCC.

Extracellular Matrix-Based Gene Expression Signature Defines Two Prognostic Subtypes of Hepatocellular Carcinoma With Different Immune Microenvironment Characteristics

Background: Accumulating evidence has suggested that the extracellular matrix (ECM) plays a vital role in the development and progression of cancer, and could be recognized as a biomarker of the response to immunotherapy. However, the effect of the ECM signature in hepatocellular carcinoma (HCC) is not well understood. Methods: HCC patients derived from the TCGA-LIHC dataset were clustered according to the ECM signature. The differences in prognosis, functional enrichment, immune infiltration, and mutation characteristics between distinct molecular clusters were examined, and its predictive value on the sensitivities to chemotherapy and immunotherapy was further analyzed. Then, a prognostic model was built based on the ECM-related gene expression pattern. Results: HCC patients were assigned into two molecular subtypes. Approximately 80% of HCC patients were classified into cluster A with poor prognosis, more frequent TP53 mutation, and lower response rate to immunotherapy. In contrast, patients in cluster B had better survival outcomes and higher infiltration levels of dendritic cells, macrophages, and regulatory T cells. The prognostic risk score model based on the expression profiles of six ECM-related genes (SPP1, ADAMTS5, MMP1, BSG, LAMA2, and CDH1) demonstrated a significant association with higher histologic grade and advanced TNM stage. Moreover, the prognostic risk score showed good performance in both the training dataset and validation dataset, as well as improved prognostic capacity compared with TNM stage. Conclusions: We characterized two HCC subtypes with distinct clinical outcomes, immune infiltration, and mutation characteristics. A novel prognostic model based on the ECM signature was further developed, which may contribute to individualized prognostic prediction and aid in clinical decision-making.

Identification of a Novel Glycosyltransferase Prognostic Signature in Hepatocellular Carcinoma Based on LASSO Algorithm.

Although many prognostic models have been developed to help determine personalized prognoses and treatments, the predictive efficiency of these prognostic models in hepatocellular carcinoma (HCC), which is a highly heterogeneous malignancy, is less than ideal. Recently, aberrant glycosylation has been demonstrated to universally participate in tumour initiation and progression, suggesting that dysregulation of glycosyltransferases can serve as novel cancer biomarkers. In this study, a total of 568 RNA-sequencing datasets of HCC from the TCGA database and ICGC database were analysed and integrated via bioinformatic methods. LASSO regression analysis was applied to construct a prognostic signature. Kaplan–Meier survival, ROC curve, nomogram, and univariate and multivariate Cox regression analyses were performed to assess the predictive efficiency of the prognostic signature. GSEA and the “CIBERSORT” R package were utilized to further discover the potential biological mechanism of the prognostic signature. Meanwhile, the differential expression of the prognostic signature was verified by western blot, qRT–PCR and immunohistochemical staining derived from the HPA. Ultimately, we constructed a prognostic signature in HCC based on a combination of six glycosyltransferases, whose prognostic value was evaluated and validated successfully in the testing cohort and the validation cohort. The prognostic signature was identified as an independent unfavourable prognostic factor for OS, and a nomogram including the risk score was established and showed the good performance in predicting OS. Further analysis of the underlying mechanism revealed that the prognostic signature may be potentially associated with metabolic disorders and tumour-infiltrating immune cells.

The Prognostic Value of Lysine Acetylation Regulators in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and mortality worldwide. lysine acetylation regulators (LARs) dynamically regulate Lysine acetylation modification which plays an important regulatory role in cancer. Therefore, we aimed to explore the potential clinical prognostic value of LARs in HCC. Methods: Differentially expressed LARs in normal liver and HCC tissues were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. To identify genes with prognostic value and establish the risk characteristics of LARs, consensus clustering was employed. We used univariate Cox regression survival analysis and LASSO Cox regression based on LARs to determine the independent prognostic signature of HCC. CIBERSORT and Gene Set Enrichment Analysis (GSEA) were used to estimate immune infiltration and functional enrichment analysis respectively. The expression of LAR was detected by Real-time quantitative polymerase chain reaction (RT-qPCR). statistical analyses were conducted using SPSS and R software. Results: In this study, the 33 LARs expression data and corresponding clinical information of HCC were obtained using TCGA and ICGC datasets. We found majority of the LARs were differentially expressed. Consensus cluster analysis was carried out based on the TCGA cohort, and three HCC subtypes (cluster 1, 2, and 3) were obtained. The LA3 subgroup had the worst clinical outcomes. Nine key LARs were identified to affect prognosis. The results showed that LARs signature has a strong independent prognostic value in HCC patients, whether in the training datasets or in the testing datasets. GSEA results showed that various tumor-related processes and pathways were abundant in the high-risk groups. RT-qPCR results showed that HAT1, HDAC1, HDAC2, HDAC4, and HDAC11 were highly expressed in HCC cells. Conclusion: Our results suggest that LARs play critical roles in HCC and are helpful for individual prognosis monitoring and clinical decision-making of HCC.

Prognostic Value of Circulating Tumour DNA in Asian Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.

Background Circulating tumour DNA (ctDNA) is a noninvasive method of detecting tumours, and its prognostic significance in hepatocellular carcinoma (HCC) patients is controversial. We conducted a systematic review of published research data to evaluate the prognostic value of ctDNA in HCC patients. Methods The PubMed, Embase, Web of Science, Cochrane Library, and Scopus databases were searched to identify eligible studies reporting disease-free survival (DFS) and overall survival (OS) stratified by ctDNA prior to January 2022. We evaluated the quality and design of these studies. The hazard ratio (HR) was used to combine the survivorship curve and univariate and multivariate results of the included studies. Results In total, 8 articles were included, encompassing 577 HCC patients. The results of survival curve analysis showed that ctDNA was related to poor OS and DFS, and the effect sizes were HR = 2.44, 95% CI (1.42, 4.20), P=0.001; HR = 2.63, 95% CI (1.96, 3.53), P < 0.001. The univariate analysis results showed that ctDNA was related to poor OS (HR = 4.48, 95% CI (1.17, 13.70), P=0.003). The combined results of multivariate analysis showed that ctDNA was related to a shorter risk of OS (HR = 3.74, 95% CI (1.45, 9.65), P=0.006). The univariate and multivariate descriptive analysis results showed that ctDNA was related to shorter DFS, and the effect sizes were HR = 3.28, 95% CI (1.23, 11.30), P=0.011; HR = 3.01, 95% CI (1.11, 10.5), P < 0.001. Conclusion The evidence provided by this analysis suggests that ctDNA may be a prognostic biomarker and is negatively correlated with the survival of HCC patients. Mutations in the TERT and SOCS3 promoters in ctDNA are associated with poor prognosis and are expected to become good targets for liquid biopsy and to help select treatment strategies.

Immune Checkpoint FGL1 Expression of Circulating Tumor Cells Is Associated With Poor Survival in Curatively Resected Hepatocellular Carcinoma.

LAG-3 is one of the common tumor immune checkpoints. LAG-3 can inhibit the activation and proliferation of T cells, and can also suppress immunity by regulating other immune-related cell functions. FGL1 was recently discovered to be the main ligand of immune checkpoint LAG-3 and play a critical role in the inhibition of T cells. However, the FGL1 expression in circulating tumor cells (CTCs) and its clinical significance in hepatocellular carcinoma (HCC) remain unclear. Therefore, this bioinformatics analysis was performed to assess the expression of FGL1 in various tumors and its association with immune infiltration. After that, CTCs from 109 HCC patients were detected and the immunofluorescence staining was performed (CD45, EpCAM, CK8/18/19, Vimentin, Twist, DAPI and FGL1). Then, we investigated FGL1 expression and EMT of CTCs and analyzed its relationship with patient survival and clinical relevance. Bioinformatic results showed that FGL1 expression was abnormal in various tumor and it was correlated with the infiltration level of several immune cells. FGL1 expression was detected in CTCs of 40 patients (36.7%). The proportion of advanced TNM stage (P<0.001) and distant metastasis(P=0.020) in FGL1 positive patients was higher than that of FGL1 negative patients. In addition, patients with FGL1 positive circulating tumor cells had worse postoperative survival than FGL1 negative patients (p=0.0297). The mixed phenotypic CTC presented a higher level of FGL1 expression than any other types, the number of which also predicted worse prognosis(p=0.0443). We also found that the expression of FGL1 on CTCs was associated with the level of FGL1 in tumor tissues. Of 12 patients receiving PD-1/PD-L1 blockade in a total of 109 cases, 8 out of 10 patients with FGL1 positive CTC showed immunotherapy resistance. It is the first study that suggested FGL1 expression in CTCs as an indicator of the poor prognosis in HCC patients. CTC detection may serve as a promising replacement for determination of tumor tissue FGL1 expression and provide evidence for the application of immunotherapy.

Prognostic and predictive value of the hypoxia-associated long non-coding RNA signature in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common cancer worldwide. Hypoxia is an important feature of solid tumors, including HCC, and is also an important factor involved in malignancy progression. However, the identification of hypoxia-related long non-coding RNA (lncRNAs) and their prognostic value in HCC have not been systematically investigated. The aim of this study is to identify the features based on the hypoxia-related lncRNAs and evaluate their predictive value for HCC prognosis. Based on the integrated analysis of HCC transcriptome data from The Cancer Genome Atlas (TCGA), we had identified 233 potential hypoxia-related lncRNAs. We further evaluated the prognostic value of these lncRNAs and optimally established a 12-lncRNA (AC012676.1, PRR7-AS1, AC020915.2, AC008622.2, AC026401.3, MAPKAPK5-AS1, MYG1-AS1, AC015908.3, AC009275.1, MIR210HG, CYTOR and SNHG3) prognostic risk model. The Cox proportional hazards regression analysis revealed that the hypoxia risk score is a novel independent prognostic predictor for HCC patients, which outperforms the traditional clinical pathological factors. Gene set enrichment analysis (GSEA) showed that the hypoxia risk score reflects the activation of biological features related to cell proliferation and the inactivation of lipid metabolism processes. In summary, we had constructed a risk score model based on 12 hypoxia-related lncRNAs, which might be a promising prognostic predictor for HCC patients and highlight their potential roles in the prevention and treatment of this malignancy.

MiR-1269a and miR-1269b: Emerging Carcinogenic Genes of the miR-1269 Family

miRNAs play an important role in the occurrence and development of human cancer. Among them, hsa-mir-1269a and hsa-mir-1269b are located on human chromosomes 4 and 17, respectively, and their mature miRNAs (miR-1269a and miR-1269b) have the same sequence. miR-1269a is overexpressed in 9 cancers. The high expression of miR-1269a not only has diagnostic significance in hepatocellular carcinoma and non-small cell lung cancer but also is related to the poor prognosis of cancer patients such as esophageal cancer, hepatocellular carcinoma, and glioma. miR-1269a can target 8 downstream genes (CXCL9, SOX6, FOXO1, ATRX, RASSF9, SMAD7, HOXD10, and VASH1). The expression of miR-1269a is regulated by three non-coding RNAs (RP11-1094M14.8, LINC00261, and circASS1). miR-1269a participates in the regulation of the TGF-β signaling pathway, PI3K/AKT signaling pathway, p53 signaling pathway, and caspase-9-mediated apoptotic pathway, thereby affecting the occurrence and development of cancer. There are fewer studies on miR-1269b compared to miR-1269a. miR-1269b is highly expressed in hepatocellular carcinoma, non-small cell lung cancer, oral squamous cell carcinoma, and pharyngeal squamous cell carcinoma, but miR-1269b is low expressed in gastric cancer. miR-1269b can target downstream genes (METTL3, CDC40, SVEP1, and PTEN) and regulate the PI3K/AKT signaling pathway. In addition, sequence mutations on miR-1269a and miR-1269b can affect their regulation of cancer. The current studies have shown that miR-1269a and miR-1269b have the potential to be diagnostic and prognostic markers for cancer. Future research on miR-1269a and miR-1269b can focus on elucidating more of their upstream and downstream genes and exploring the clinical application value of miR-1269a and miR-1269b.At present, there is no systematic summary of the research on miR-1269a and miR-1269b. This paper aims to comprehensively analyze the abnormal expression, diagnostic and prognostic value, and molecular regulatory pathways of miR-1269a and miR-1269b in multiple cancers. The overview in our work can provide useful clues and directions for future related research.

Identification of an EMT-related lncRNA signature and LINC01116 as an immune-related oncogene in hepatocellular carcinoma.

Background: Epithelial–mesenchymal transition (EMT) plays a critical role in the recurrence and metastasis of hepatocellular carcinoma (HCC). Some long noncoding (lnc)RNAs are involved in this process through the regulation of EMT-related transcription factors.Methods: In this study, we established a novel EMT-related lncRNA signature in HCC and identified hub lncRNAs that can serve as potential therapeutic targets. Differentially expressed lncRNAs were identified by screening HCC patient data from The Cancer Genome Atlas, and a correlation analysis was performed to identify those associated with EMT. The EMT-related lncRNA signature was established by univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. After verifying the prognostic accuracy of the signature, its relationships to immune cell infiltration and immune checkpoint targets were explored. LINC01116 was identified as a hub lncRNA and its role in HCC was investigated in vitro and in vivo.Results: A 5-lncRNA signature was developed for HCC and its prognostic accuracy was assessed by survival, time-dependent receiver operating characteristic curve, clinical correlation, and Cox regression analyses. The correlation analysis showed that the lncRNA signature was closely related to immune cell infiltration and 10 immune checkpoint targets and also predicted the prognosis of HCC patients with high accuracy. In vitro and in vivo experiments revealed that LINC01116 stimulated cell proliferation, cell cycle progression, and tumor metastasis. We also found that LINC01116 was closely related to immune regulation.Conclusions: These results demonstrate that LINC01116 is an immune-related oncogene that is associated with both EMT and immune regulation in HCC. Moreover, the EMT-related lncRNA signature that includes LINC01116 can guide risk stratification and clinical decision-making in HCC management.

Ferroptosis Regulator Modification Patterns and Tumor Microenvironment Immune Infiltration Characterization in Hepatocellular Carcinoma.

Accumulating studies have highlighted the biologic significances of ferroptosis modification in tumor progression, but little is known whether ferroptosis modification patterns have potential roles in tumor microenvironment (TME) immune cell infiltration of hepatocellular carcinoma (HCC). In this study, we evaluated 51 ferroptosis regulators and performed consensus clustering algorithm to determine ferroptosis modification patterns and the ferroptosis related gene signature in HCC. Gene set variation analysis (GSVA) was employed to explore biological molecular variations in distinct ferroptosis modification patterns. Single sample gene set enrichment analysis (ssGSEA) algorithm was performed to quantify the relative infiltration levels of various immune cell subsets. Principal component analysis (PCA) algorithm was used to construct the ferroptosisSig score to quantify ferroptosis modification patterns of individual tumors with immune responses. Three distinct ferroptosis modification patterns were identified. GSVA enrichment analysis indicated that three ferroptosis modification subgroups were enriched in different metabolic pathways. ssGSEA analysis determined that 19 of 24 immune infiltrating cells had significant differences in three distinct ferroptosis patterns. A 91-ferroptosis gene signature was constructed to stratify patients into two ferroptosisSig score groups. Patients in the higher ferroptosisSig score were characterized by significantly prolonged survival time compared with patients in the lower ferroptosisSig score group (p < .0001). An immunotherapy cohort confirmed patients with higher ferroptosisSig score determined significant therapeutic advantages and clinical benefits. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of anti-PD/L1 immunotherapy by ferroptosisSig score. Our study indicated the ferroptosis modification played a significant role in TME heterogeneity and complexity. Evaluating the ferroptosis modification pattern of individual tumor could strengthen our cognition of TME infiltration characteristics and guide more effective clinic immunotherapy strategies.

Clinical Significance and Potential Role of LSM4 Overexpression in Hepatocellular Carcinoma: An Integrated Analysis Based on Multiple Databases.

Background: Hepatocellular carcinoma (HCC) is a solid tumor with high recurrence rate and high mortality. It is crucial to discover available biomarkers to achieve early diagnosis and improve the prognosis. The effect of LSM4 in HCC still remains unrevealed. Our study is dedicated to exploring the expression of LSM4 in HCC, demonstrating its clinical significance and potential molecular mechanisms. Methods: Clinical information and LSM4 expression values of HCC were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Survival analysis and receiver operating characteristic (ROC) curve analysis were applied to evaluate the prognostic and diagnostic significance of LSM4. Calculating pooled standardized mean difference (SMD) and performing summary receiver operating characteristic (sROC) curve analysis to further determine its expression status and diagnostic significance. LSM4-related co-expressed genes (CEGs) were obtained and explored their clinical significance in HCC. LSM4-associated pathways were identified through Gene set enrichment analysis (GSEA). Results: Up-regulated LSM4 was detected in HCC tissues (SMD = 1.56, 95% CI: 1.29–1.84) and overexpressed LSM4 had excellent distinguishing ability (AUC = 0.91, 95% CI: 0.88–0.93). LSM4 was associated with clinical stage, tumor grade, and lymph node metastasis status (p < 0.05). Survival analysis showed that high LSM4 expression was related to poor overall survival (OS) of HCC patients. Cox regression analysis suggested that high LSM4 expression may be an independent risk factor for HCC. We obtained nine up-regulated CEGs of LSM4 in HCC tissues, and six CEGs had good prognostic and diagnostic significance. GSEA analysis showed that up-regulated LSM4 was closely related to the cell cycle, cell replication, focal adhesion, and several metabolism-associated pathways, including fatty acid metabolism. Conclusion: Overexpressed LSM4 may serve as a promising diagnostic and prognostic biomarker of HCC. Besides, LSM4 may play a synergistic effect with CEGs in promoting the growth and metastasis of HCC cells via regulating crucial pathways such as cell cycle, focal adhesion, and metabolism-associated pathways.

Prognostic Implication of a Novel Four Pyroptosis-Associated Gene Signature in Hepatocellular Carcinoma

Prognostic Implication of a Novel Four Pyroptosis-Associated Gene Signature in Hepatocellular Carcinoma

Overexpression of BACH1 mediated by IGF2 facilitates hepatocellular carcinoma growth and metastasis via IGF1R and PTK2.

Background: Accumulating studies manifest that BTB and CNC homology 1 (BACH1) facilitates multiple malignancies progression and metastasis, and targeting the BACH1 pathway enhances antitumor efficacy. Nevertheless, the exact mechanism of BACH1 promoting growth and metastasis and its therapeutic significance in hepatocellular carcinoma (HCC) remain unclear.Methods: The expression of BACH1 in human HCC specimens and HCC cell lines was analyzed by quantitative RT-PCR (RT-qPCR), western blot, and immunohistochemistry (IHC). The invasiveness and metastasis of HCC cells in vitro and in vivo were evaluated using transwell assays and orthotopic xenograft models. The luciferase reporter assays and chromatin immunoprecipitation (ChIP) assays were performed to explore the transcriptional regulation of insulin-like growth factor 1 receptor (IGF1R) and protein tyrosine kinase 2 (PTK2) by BACH1.Results: BACH1 was prominently upregulated in human HCC samples and elevated BACH1 expression was associated with poor overall survival (OS) and high recurrence rates of HCC patients. BACH1 facilitated growth and metastasis of HCC by upregulating cell motility-related genes IGF1R and PTK2. Notably, insulin-like growth factor 2 (IGF2), the ligand of IGF1R, in turn upregulated BACH1 expression through the IGF1R-ERK1/2-ETS1 cascades, thus forming a positive feedback loop to provoke HCC growth and metastasis. Moreover, combining IGF1R inhibitor linsitinib with PTK2 inhibitor defactinib prominently suppressed BACH1-mediated HCC growth and metastasis.Conclusions: These results demonstrated the tumorigenic and pro-metastatic role of BACH1 in HCC, which could be a promising biomarker for predicting poor prognosis and selecting patients who could benefit from combination therapy of IGF1R-targeted and PTK2-directed.

ARID1A expression in hepatocellular carcinoma and relation to tumor recurrence after microwave ablation.

Aim of the studyAT-rich interactive domain 1A (ARID1A) is a subunit of the switch/sucrose non-fermentable chromatin remodeling complex, which is commonly mutated in human cancers. The clinical and pathological significance of ARID1A alteration in hepatocellular carcinoma (HCC) has not yet been clarified. The present study aimed to evaluate the clinical significance of the ARID1A gene signature in HCC and its relation to the likelihood of tumor recurrence after microwave ablation (MWA).Material and methodsThis study included 50 patients with cirrhotic HCC of Barcelona Clinic Liver Cancer stages 0/A eligible for MWA. Tumor and peri-tumor biopsies were obtained just prior to MWA and assessed for tumor pathological grade and ARID1A expression by immunohistochemistry. Patients were followed for one year after complete tumor ablation to detect any recurrence.ResultsTumor size (MCp = 0.010) and α-fetoprotein level (p = 0.013) can effectively predict the response to MWA. Nuclear expression of ARID1A was significantly lower in HCC compared to the corresponding peri-tumor cirrhotic liver tissues (p = 0.002), but no significant difference in ARID1A cytoplasmic expression was found. Nuclear ARID1A expression level in HCC showed a significantly negative relation to tumor size (MCp = 0.006), pathological grade (MCp = 0.046) and post-MWA tumor recurrence (FEp = 0.041).ConclusionsARID1A loss may enhance HCC aggressiveness and post-MWA tumor recurrence. ARID1A could be a potential target to select HCC patients for future therapies.

A novel immune checkpoint-related gene signature for hepatocellular carcinoma to predict clinical outcomes and therapeutic response.

Immune checkpoint genes (ICGs) have recently been proven to perform instrumental functions in the maintenance of immune homeostasis and represent a promising therapeutic strategy; however, their expression patterns and prognostic values are not fully elucidated in hepatocellular carcinoma (HCC). In this investigation, we focused on establishing and validating a prognostic gene signature to facilitate decision-making in clinical practice. Clinical information, as well as transcriptome data, was obtained from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox method were employed to build a multi-gene signature in the TCGA database, while the ICGC database was used for validation. Subsequently, utilizing the six-gene signature, we were able to categorize patients into high- and low-risk groups. In two cohorts, survival analysis findings revealed a dismal outlook for the high-risk group. The receiver operating characteristic curves were utilized to estimate the gene signature's prediction ability. Moreover, correlation analysis showed high-risk group was linked to advanced pathological stage, infiltration of immune cells and therapeutic response. In summary, this unique gene profile might serve not only as a useful prognostic indicator but also as a marker of therapy responsiveness in HCC.

The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and lethal types of cancer. This study aimed to identify the expression regulatory network and a prognostic signature of HCC. RNA-seq data from The Cancer Genome Atlas were used to identify the differentially expressed genes (DEGs) between HCC and normal liver tissues. DEGs were subjected to the construction of protein-protein interaction (PPI) network and enrichment analysis of Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The results showed that most of the DEGs were enriched in the cell cycle pathway, and the top 10 hub genes in the PPI network belong to the cell cycle pathway. A ceRNA network was constructed using starBase database, including one lncRNA (SNHG1), seven miRNAs (miR-195-5p, miR-199a-3p, miR-199a-5p, miR-199b-3p, miR-383-5p, miR-424-5p and miR-654-3p) and six of the top 10 hub genes (BUB1, CCNA2, CCNB1, KIF11, NCAPG, and TOP2A). In vitro experiments showed that knockdown of SNHG1 in the HCC cell lines (Huh7 and HepG2) decreased the expression of the six hub genes and cell viability, leading to cell cycle arrest at the G1 phase. These findings indicate that SNHG1 promotes cell proliferation by regulating cell cycle-related genes as a ceRNA. Additionally, Kaplan-Meier's survival and multivariate Cox regression analysis identified a prognostic signature of seven genes (including SNHG1 and the six SNHG1-regulated hub genes) for overall survival of HCC patients. In conclusion, this study identified a novel regulatory network in HCC and a potential independent prognostic factor for overall survival of HCC patients.

Screening of a novel autophagy-related prognostic signature and therapeutic targets in hepatocellular carcinoma.

Many studies have indicated that autophagy plays an important role in multiple cancers, including hepatocellular carcinoma (HCC). This study aimed to establish a prognostic signature for HCC based on autophagy-related genes (ARGs) to predict the prognosis of patients. The list of ARGs was derived from screening National Center for Biotechnology Information (NCBI)-Gene and Molecular Signatures Database (MSigDB) datasets. Differential analysis was conducted via the R limma package in HCC patients based on The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analysis were conducted to identify key prognostic ARGs via the survival package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by clusterProfiler package. The Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to conduct immune analysis. Finally, the correlation between the prognostic model and clinical characteristics was also assessed, including age, tumor-node-metastasis (TNM) stages, and tumor grades. Firstly, 106 differential ARGs were identified and 10 candidates were further confirmed via Cox regression analysis, including BAMBI, HIF1A, SERPINE1, EZH2, SLC9A3R1, IGFBP3, HSPB8, DAB2, CXCL1 and PRNP. The receiver operating characteristic (ROC) curve analysis revealed that the ARGs risk model had a well diagnostic positive rate with 1-year area under the curve (AUC)=0.688 and 3-year AUC=0.674. Correlation analysis indicated that only advanced tumor stages were positively associated with high ARGs scores with P=0.0227. There were also significant differences in tumor purity (P=6.71e-05), infiltrating cell analysis (P=7.77e-05), immune analysis (P=7.9e-05), and stromal cells analysis (P=0.0015) in high- and low-risk ARGs samples. The genes HIF1A, IGFBP3, and DAB2 were found to have high frequent missense mutations in samples with high-risk ARGs scores. Lastly, we also established a nomogram to predict overall survival (OS) of HCC by integrating ARGs scores and other clinical parameters. Our study established an autophagy-related signature for predicting the prognosis of HCC patients, providing a thorough understanding of the underlying mechanisms of autophagy in HCC.

Identification of molecular subtypes and prognostic signature for hepatocellular carcinoma based on genes associated with homologous recombination deficiency

Hepatocellular carcinoma (HCC) is a rapidly developing digestive tract carcinoma. The prognosis of patients and side effects caused by clinical treatment should be better improved. Nonnegative matrix factorization (NMF) clustering was performed using 109 homologous recombination deficiency (HRD)-related of HCC genes from The Cancer Genome Atlas (TCGA) database. Limma was applied to analyze subtype differences. Immune scores and clinical characteristics of different subtypes were compared. An HRD signature were built with least absolute shrinkage operator (LASSO) and multivariate Cox analysis. Performance of the signature system was then assessed by Kaplan–Meier curves and receiver operating characteristic (ROC) curves. We identified two molecular subtypes (C1 and C2), with C2 showing a significantly better prognosis than C1. C1 contained 3623 differentially expressed genes. A 4-gene prognostic signature for HCC was established, and showed a high predicting accuracy in validation sets, entire TCGA data set, HCCDB18 and GSE14520 queues. Moreover, the risk score was validated as an independent prognostic marker for HCC. Our research identified two molecular subtypes of HCC, and proposed a novel scoring system for evaluating the prognosis of HCC in clinical practice.

Expression of SET domain bifurcated histone lysine methyltransferase 1 and its clinical prognostic significance in hepatocellular carcinoma.

BackgroundTo detect the expression of histone methyltransferase SETDB1 in hepatocellular carcinoma, and to analyze the relationship between SETDB1 expression and tumor size, microvascular invasion, pTNM stage, gender, age, tumor number, tumor differentiation, and other clinicopathological characteristics.MethodsImmunohistochemical method was used to detect the expression of SETDB1 proteins in liver cancer tissues and adjacent tissues of 100 cases. The qRT‐PCR method was used to detect the expression of SETDB1 mRNA in hepatocellular carcinoma and adjacent tissues of 64 cases.ResultsThe expression of SETDB1 protein and mRNA in hepatocellular carcinoma was higher than that of adjacent normal liver tissue (p < 0.05). High protein expression of SETDB1 was associated with tumor size, MVI presence, and pTNM stage (p < 0.05). Univariate analysis revealed that the tumor size, tumor differentiation, MVI grade, and pTNM stage were correlated with DFS, while tumor size, MVI grade, pTNM stage, and SETDB1 protein expression were correlated with OS. Multivariate analysis showed that the combination of MVI grade and pTNM stage has statistical significance in predicting prognosis, while SETDB1 protein expression was not significant prognosis factor.ConclusionsSETDB1 has a certain role in HCC progression and may act as a prognostic predictor concerning the survival of HCC patients.