The Cancer Genome Atlas Liver Hepatocellular Carcinoma Research Articles

Prognostic effect of DNA methylation of BTG2 gene in Chinese hepatocellular carcinoma

BackgroundThis study aims to develop a prognostic model for overall survival based on potential methylation sites within B-cell translocation gene 2 (BTG2) in Chinese patients with hepatocellular carcinoma (HCC). MethodsThis is a retrospective study. The beta values of nine CpG sites and RSEM normalized count values of BTG2 gene were extracted from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (TCGA-LIHC) dataset, with the beta value representing the methylation level by indicating the ratio of the intensity of the methylated bead type to the combined locus intensity. Pyrosequencing was performed to determine the range of methylation values surrounding cg01798157 site in BTG2 gene. A weighted linear model was developed to predict the overall survival (OS). ResultsThe beta value of cg01798157 was significantly negatively associated with the mRNA expression of BTG2 in the TCGA-LIHC dataset (Spearman's rho = −0.5306, P = 2.27 × 10−27). The methylation level of cg01798157 was significantly associated with OS in the cohort of 51 Chinese HCC patients (Hazard ratio = 0.597, 95% CI: 0.434–0.820, P = 0.001). Multivariate Cox regression analysis identified methylation level of cg01798157, cirrhosis, and microvascular invasion as independent prognostic factors. The prognostic efficiency of death risk score was superior to that of cirrhosis or microvascular invasion alone. ConclusionsThe methylation level of cg01798157 in BTG2 may be an epigenetic biomarker in Chinese patients with resectable HCC.

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BackgroundMost of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients. MethodsWe collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). ResultsIn predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556–0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction. ConclusionsOur results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.

Abstract 425: GPD1L participates in glycerol-3-phosphate biogenesis and promotes tumor initiation and invasion in hepatocellular carcinoma

Abstract Background: Metabolic reprogramming in hepatocellular carcinoma (HCC) has received rising interest. However, current studies often focus on fatty acid de novo synthesis or oxidation, but less on glycerolipids metabolism. Interestingly, in HCC, we observed frequent dysregulation in enzymes responsible for glycerol-3-phosphate shuttle, which potentially links glycolysis and glycerolipids metabolism. Hence, we aimed to identify the functional significance of glycerol-3-phosphate dehydrogenase 1 like (GPD1L), an enzyme for the shuttle, and its regulation of expression in HCC. Methods: We utilized transcriptomic analysis of clinical HCC samples to validate the frequent overexpression of GPD1L in tumor cells and examined its association with clinicopathological features. In vitro and in vivo assays were performed to explore the functional significance of GPD1L in HCC initiation and progression. Furthermore, with targeted metabolomics analysis, we investigated the role of GPD1L in glycerol-3-phosphate shuttle in HCC. We also performed promoter study to understand the transcriptional regulation on GPD1L expression. Results: Among GPD family members, GPD1L was consistently upregulated at mRNA level in clinical HCC samples in The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (N=50) and our in-house RNA-sequencing cohorts (N=41), and in a separate independent in-house cohort as examined by RT-qPCR (N=80). GPD1L overexpression was associated with increased tumor invasiveness (p=0.008) and poorer overall survival (p=0.0017) in HCC patients. Functionally, knockdown of GPD1L suppressed HCC migration (fold change ≤ 0.43) and invasion (fold change ≤ 0.40). GPD1L knockdown also inhibited tumor initiation abilities, as shown by reduced colony (fold change ≤ 0.37) and sphere formation (fold change ≤ 0.41) in vitro, and lower stem cell frequency (p=1.96e-9) in vivo. Furthermore, GPD1L knockdown enhanced sensitivity of HCC cells to chemotherapeutic drugs, sorafenib and doxorubicin. Metabolically, GPD1L facilitated synthesis of glycerolipids precursor, glycerol-3-phosphate (G3P) from glycolysis intermediate dihydroxyacetone phosphate (DHAP) in HCC. Lastly, with chromatin-immunoprecipitation and Luciferase reporter assays, we demonstrated ELF1 bound to GPD1L promoter directly to enhance the gene transcription, while knockdown of ELF1 suppressed GPD1L mRNA and protein expression. Conclusion: Our study demonstrated the overexpression of the glycolysis-related gene, GPD1L, in HCC. GPD1L promoted tumor initiation, invasion and chemoresistance, and in turn might lead to worse clinical outcome. Metabolically, it was responsible for DHAP-to-G3P conversion in HCC and might serve as a linkage between glycolysis and glycerolipid metabolism. Our results also identified the novel role of ELF1 as the transcriptional activator of GPD1L in HCC. Citation Format: Tiffany Ching-Yun Yu, Luqing Zhao, Lu Tian, Charles Shing Kam, Joyce Man-Fong Lee, Daniel Wai-Hung Ho, Lo-Kong Chan, Yu-Man Tsui, Karen Man-Fong Sze, Irene Oi-Lin Ng. GPD1L participates in glycerol-3-phosphate biogenesis and promotes tumor initiation and invasion in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 425.

Abstract 1637: EPHB4 is a key regulator of G1/S transition in hepatocellular carcinoma

Abstract Effective therapeutic regimens against advanced hepatocellular carcinoma (HCCs) have recently improved but it remains very limited. Targeting receptor tyrosine kinases (RTKs) has proven to one of the main ways of achieving better survival outcome in HCC patients, yet the precise mechanism for this success remains to be elusive. We have systematically investigated the expression profiles of RTKs transcriptomic datasets i.e. The Cancer Genome Atlas - Liver hepatocellular carcinoma (TCGA-LIHC) (n=371) and our in-house cohort of paired i.e. HKU-QMH (n=41), and identified EPHB4 as one of the most abundantly expressed and frequently mutated RTKs in human HCCs. EPHB4 expression was found to be significantly correlated with Alpha Fetoprotein (AFP) expression, a factor commonly used in the diagnosis of HCCs. Furthermore, EphB4 has been demonstrated to play a regulatory role in VEGF/VEGFR-mediated angiogenesis, critical targets for current successful drugs. We confirmed abundant membrane EphB4 expression in HCC clinical specimens and human HCC cell line models using immunohistochemistry. Clinicopathological correlation analysis of EPHB4 mRNA expression revealed that its overexpression is associated with aggressive tumor features including presence of tumor microsatellite, liver invasion, venous invasion, and absence of tumor encapsulation. Functionally, stably knocking down EPHB4 (shEPHB4) resulted in a strong reduction of proliferation and self-renewal rates of multiple HCC cell lines in vitro. It significantly reduced tumor growth rates in subcutaneous and liver orthotopic models in vivo. Furthermore, limiting dilution assay showed EPHB4 plays a role in tumor initiation property of HCC cells. Mechanistically, we performed Gene Set Enrichment Analysis (GSEA) of transcriptome profiles for shEPHB4 with respective controls and found that knocking down EPHB4 causes HCC cells undergo drastic changes in several cell cycle checkpoints including G1/S transition. Using thymidine blockade, we further confirmed that knockdown of significantly hinders the transition of HCC cells from G1 to S phase of cell cycle. Our data suggests a strong link between EphB4 and cell cycle. Conclusion: We found EphB4 plays a functional role in regulating G1/S transition in human HCCs and understanding regulatory role of EphB4 on cell cycle progression may provide mechanistic insights into the how to effectively target HCC in the clinic. Citation Format: Abdullah Husain, Elley Y. Chiu, Hoi-Tang Ma, Daniel W. Ho, Karen M. Sze, Lo-Kong Chan, Irene O. Ng. EPHB4 is a key regulator of G1/S transition in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1637.

Prognostic PET [11C]-acetate uptake is associated with hypoxia gene expression in patients with late-stage hepatocellular carcinoma – a bench to bed study

BackgroundPositron Emission Tomography (PET) with combined [18F]-FDG and [11C]-acetate (dual-tracer) is used for the management of hepatocellular carcinoma (HCC) patients, although its prognostic value and underlying molecular mechanism remain poorly understood. We hypothesized that radiotracer uptake might be associated with tumor hypoxia and validated our findings in public and local human HCC cohorts.MethodsTwelve orthotopic HCC xenografts were established using MHCC97L cells in female nude mice, with 5 having undergone hepatic artery ligation (HAL) to create tumor hypoxia in vivo. Tumors in both Control and HAL-treated xenografts were imaged with [11C]-acetate and [18F]-FDG PET-MR and RNA sequencing was performed on the resected tumors. Semiquantitative analysis of PET findings was then performed, and the findings were then validated on the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and patients from our institution.ResultsHAL-treated mice showed lower [11C]-acetate (HAL-treated vs. Control, tumor-to-liver SUV ratio (SUVTLR): 2.14[2.05–2.21] vs 3.11[2.75–5.43], p = 0.02) but not [18F]-FDG (HAL-treated vs. Control, SUVTLR: 3.73[3.12–4.35] vs 3.86[3.7–5.29], p = 0.83) tumor uptakes. Gene expression analysis showed the PET phenotype is associated with upregulation of hallmark hypoxia signature. The prognostic value of the hypoxia gene signature was tested on the TCGA-LIHC cohort with upregulation of hypoxia gene signature associated with poorer overall survival (OS) in late-stage (stage III and IV) HCC patients (n = 66, OS 2.05 vs 1.67 years, p = 0.046). Using a local cohort of late-stage HCC patients who underwent dual-tracer PET-CT, tumors without [11C]-acetate uptake are associated with poorer prognosis (n = 51, OS 0.25 versus 1.21 years, p < 0.0001) and multivariable analyses showed [11C]-acetate tumor uptake as an independent predictor of OS (HR 0.17 95%C 0.06–0.42, p < 0.0001).Conclusions[11C]-acetate uptake is associated with alteration of tumor hypoxia gene expression and poorer prognosis in patients with advanced HCC.

Cuproptosis-related molecular classification and gene signature of hepatocellular carcinoma and experimental verification.

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor overall prognosis. Cuproptosis, a recently proposed mode of copper-dependent cell death, plays a critical role in the malignant progression of various tumors; however, the expression and prognostic value of cuproptosis-related regulatory genes in HCC remain unclear. Genomic, genetic, and expression profiles of ten key cuproptosis-related regulatory genes were analyzed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset and protein expression data from the Human Protein Atlas (HPA) database. Unsupervised clustering of HCC patients based on these ten key cuproptosis-related regulatory genes was used to identify different HCC subtypes and analyze the differences in clinical and immune characteristics among subtypes. Subsequently, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox analyses were used to establish a cuproptosis-related prognostic signature, and the accuracy of prognostic signature prediction was internally validated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curve in TCGA training and testing cohorts. The prognostic signature was externally validated using TCGA-LIHC entire cohort and International Cancer Genome Consortium Liver Cancer (ICGC-LIRI) cohorts. Finally, the expression landscape of cuproptosis-related regulatory genes in prognostic signature was explored by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry (IHC) experiments. Ten cuproptosis-related genes were differentially expressed in normal and HCC tissues. Unsupervised clustering identified two subtypes and HCC patients with these two subtypes had different clinical prognoses and immune characteristics, as well as different degrees of response to immunotherapy. Lipoyltransferase 1 (LIPT1), dihydrolipoamide s-acetyltransferase (DLAT), and cyclin dependent kinase inhibitor 2A (CDKN2A) were selected to construct a prognostic signature, which significantly distinguished HCC patients with different survival periods in the TCGA training and testing cohorts and was well validated in both the TCGA-LIHC entire cohort and ICGC-LIRI cohort. The risk score of the prognostic signature was confirmed to be an independent prognostic factor, and nomograms were generated to effectively predict the probability of HCC patient survival. The qRT-PCR, western blotting and IHC results also revealed a significant imbalance in the expression of these cuproptosis-related genes in HCC. The classification and prognostic signature based on cuproptosis-related regulatory genes helps to explain the heterogeneity of HCC, which may contribute to the individualized treatment of patients with the disease.

Development and validation of a chromatin regulator signature for predicting prognosis hepatocellular carcinoma patient.

Hepatocellular carcinoma (HCC) is a malignancy with a bleak prognosis. Although emerging research increasingly supports the involvement of chromatin regulators (CRs) in cancer development, CRs in HCC patients have not received proportionate attention. This study aimed to investigate the role and prognostic significance of CRs in HCC patients, providing new insights for clinical diagnosis and treatment strategies. We analyzed 424 samples in The Cancer Genome Atlas-Liver hepatocellular carcinoma (TCGA-LIHC) data to identify key CR genes associated with HCC prognosis by differential expression and univariate Cox regression analyses. LASSO-multivariate Cox regression method was used for construction of a prognostic signature and development of a CR-related prognosis model. The prognosis capacity of the model was evaluated via Kaplan-Meier method. Relationship between the model and tumor microenvironment (TME) was evaluated. Additionally, clinical variables and the model were incorporated to create a nomogram. The role of the prognostic gene MRG-binding protein (MRGBP) in HCC was elucidated by immunohistochemistry and semiquantitative analysis. A risk score model, comprising B-lymphoma Mo-MLV insertion region 1 (BMI1), chromobox 2 (CBX2), and MRGBP, was constructed. The area under the curve (AUC) of the CR-based signature is 0.698 (P<0.05), exhibiting robust predictive power. Functional and pathway analyses illuminated the biological relevance of these genes. Immune microenvironment analysis suggested potential implications for immunotherapy. Drug sensitivity analysis identified agents for targeted treatment. Clinical samples show that MRGBP is highly expressed in HCC tissues. This CR-based signature shows promise as a valuable prognostic tool for HCC patients. It demonstrates predictive capabilities, independence from other clinical factors, and potential clinical applicability. In addition, we need more experiments to validate our findings. These findings offer insights into HCC prognosis and treatment, with implications for personalized medicine and improved patient outcomes.

Recurrence risk stratification of hepatocellular carcinomas based on immune gene expression and features extracted from pathological images.

Immune-based therapy is a promising type of treatment for hepatocellular carcinoma (HCC) but has only been partially successful due to the high heterogeneity in HCC tumor. The differences in the degree of tumor cell progression and in the activity of tumor immune microenvironment could lead to varied clinical outcome. Accurate subgrouping for recurrence risk is an approach to address the issue of such heterogeneity. It remains under investigation as whether integrating quantitative whole slide image (WSI) features with the expression profile of immune marker genes can improve the risk stratification, and whether clinical outcome prediction can assist in understanding molecular biology that drives the outcome. We included a total of 231 patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) project. For each patient, we extracted 18 statistical metrics corresponding to a global region of interest and 135 features regarding nucleus shape from WSI. A risk score was developed using these image features with high-dimensional survival modeling. We also introduced into the model the expression profile of 66 representative marker genes relevant to currently available immunotherapies. We stratified all patients into higher and lower-risk subgroup based on the final risk score selected from multiple models generated, and further investigated underlying molecular mechanisms associated with the risk stratification. One WSI feature and three immune marker genes were selected into the final recurrence-free survival (RFS) prediction model following the best integrated modeling framework. The resultant score showed a significantly improved prediction performance on the test dataset (mean time-dependent AUCs = 0.707) as compared to those of other types (e.g: mean time-dependent AUCs of AJCC tumor stage = 0.525) of input data integration. To assess that the risk score could provide a higher-resolution risk stratification, a lower-risk subgroup (or a higher-risk subgroup) was arbitrarily assigned according to score falling below (or above) the median score. The lower risk subgroup had significantly longer median RFS time than that of the higher-risk patients (median RFS = 903 vs. 265 days, log-rank test p-value< 0.0001). Additionally, the higher-risk subgroup, in contrast to the lower-risk patients were characterized with a significant downregulation of immune checkpoint genes, suppressive signal in tumor immune response pathways, and depletion of CD8 T cells. These observations for the higher-risk subgroup suggest that new targets for adoptive or checkpoint-based combined systemic therapies may be useful. We developed a novel prognostic model to predict RFS for HCC patients, using one feature that can be automatically extracted from routine histopathological images, as well as the expression profiles of three immune marker genes. The methodology used in this paper demonstrates the feasibility of developing prognostic models that provide both useful risk stratification along with valuable biological insights into the underlying characteristics of the subgroups identified.

Increased hsa-miR-100-5p Expression Improves Hepatocellular Carcinoma Prognosis in the Asian Population with PLK1 Variant rs27770A>G.

Hepatocellular carcinoma (HCC) has the highest incidence and mortality in the Asian population, and race is an independent risk factor affecting survival time in liver cancer. Micro RNAs (miRNAs) are remarkably dysregulated in HCC and closely associated with HCC prognosis. Recent studies show that genetic variability between ethnic groups may result in differences in the specificity of HCC miRNA biomarkers. Here, we reveal a high expression level of hsa-miR-100-5p, an HCC prognosis-related miRNA, which improves HCC prognosis in the Asian Population with Polo-like kinase 1 (PLK1) variant rs27770A>G. In this study, we discovered that hsa-miR-100-5p was downregulated in various HCC cell lines. While mimics transient transfection and mouse liver cancer model confirmed the interaction between hsa-miR-100-5p and PLK1, a stratified analysis based on the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data suggest both low hsa-miR-100-5p expression level and high PLK1 expression level associated with poor HCC prognosis, especially in the Asian population. According to the 1000 Genomes Project database, the SNP rs27770 located in 3'UTR of PLK1 had a significantly higher G allele frequency in the East Asian population. Bioinformatics analysis suggested that rs27770 A>G affects PLK1 mRNA secondary structure and alters the hsa-miR-100-5p/PLK1 interaction by forming an additional seedless binding site. This racial variation caused PLK1 to be more vulnerable to hsa-miR-100-5p inhibition, resulting in hsa-miR-100-5p being more favorable for HCC prognosis in the Asian population.

Cathepsin V is correlated with the prognosis and tumor microenvironment in liver cancer.

Recent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer. We downloaded transcriptomic profiles of the cancer genome atlas-liver hepatocellular carcinoma (TCGA-LIHC) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle-related differentially expressed prognostic genes and identified CENPA, CDC20, and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA-LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues. We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA-LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single-gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and is associated with the effectiveness of hepatocellular carcinoma treatment. In couclusion, CTSV is a novel cell cycle-associated gene with clinical significance in HCC.

High CD49a+ NK cell infiltrate is associated with poor clinical outcomes in Hepatocellular Carcinoma

NK cells infiltrating Hepatocellular Carcinoma (HCC) may express residency markers such as Integrin Subunit Alpha 1 (CD49a) that have been associated with nurturing functions in the decidua, and characterized by the production of angiogenic factors as well as loss of cytotoxicity. CIBERSORT, a computational analysis method for quantifying cell fractions from bulk tissue gene expression profiles, was used to estimate the infiltrating immune cell composition of the tumor microenvironment from gene expression profiles of a large cohort of 225 HCCs in the public GEO database. Decidual-like CD49a+ NK cells, in addition to another 22 immune cell populations, were characterized and thoroughly investigated so that HCC cell heterogeneity in a large cohort of 225 HCCs from the public GEO database could be studied. An inverse correlation of the expression of CD49a+ NK-cells and CD8+ T-cells suggested a negative association with clinical outcomes. This result was confirmed in a further validation cohort of 100 HCC patients from The Cancer Genome Atlas, Liver Hepatocellular Carcinoma (TCGA-LIHC). Cox regression analysis did not identify CD49a+ cells as a variable independently associated with survival. However, a more abundant infiltrate of this subset was present in patients at a more advanced pathological and clinical HCC stage. In conclusion, we found that NK cells, with a decidual-like gene expression profile, are enriched in HCC, and their abundance increases not only in tumor size but also at advanced stages of the disease suggesting that these cells play a role in tumor growth. For this reason, these NK cells may represent a possible new target for immunotherapeutic approaches in HCC.

Novel Molecular Subtyping Scheme Based on In Silico Analysis of Cuproptosis Regulator Gene Patterns Optimizes Survival Prediction and Treatment of Hepatocellular Carcinoma.

The liver plays an important role in maintaining copper homeostasis. Copper ion accumulation was elevated in HCC tissue samples. Copper homeostasis is implicated in cancer cell proliferation and angiogenesis. The potential of copper homeostasis as a new theranostic biomarker for molecular imaging and the targeted therapy of HCC has been demonstrated. Recent studies have reported a novel copper-dependent nonapoptotic form of cell death called cuproptosis, strikingly different from other known forms of cell death. The correlation between cuproptosis and hepatocellular carcinoma (HCC) is not fully understood. The transcriptomic data of patients with HCC were retrieved from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and were used as a discovery cohort to construct the prognosis model. The gene expression data of patients with HCC retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases were used as the validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to construct the prognosis model. A principal component analysis (PCA) was used to evaluate the overall characteristics of cuproptosis regulator genes and obtain the PC1 and PC2 scores. Unsupervised clustering was performed using the ConsensusClusterPlus R package to identify the molecular subtypes of HCC. Cox regression analysis was performed to identify cuproptosis regulator genes that could predict the prognosis of patients with HCC. The receiver operating characteristics curve and Kaplan-Meier survival analysis were used to understand the role of hub genes in predicting the diagnosis and prognosis of patients, as well as the prognosis risk model. A weighted gene co-expression network analysis (WGCNA) was used for screening the cuproptosis subtype-related hub genes. The functional enrichment analysis was performed using Metascape. The 'glmnet' R package was used to perform the LASSO regression analysis, and the randomForest algorithm was performed using the 'randomForest' R package. The 'pRRophetic' R package was used to estimate the anticancer drug sensitivity based on the data retrieved from the Genomics of Drug Sensitivity in Cancer database. The nomogram was constructed using the 'rms' R package. Pearson's correlation analysis was used to analyze the correlations. We constructed a six-gene signature prognosis model and a nomogram to predict the prognosis of patients with HCC. The Kaplan-Meier survival analysis revealed that patients with a high-risk score, which was predicted by the six-gene signature model, had poor prognoses (log-rank test p < 0.001; HR = 1.83). The patients with HCC were grouped into three distinct cuproptosis subtypes (Cu-clusters A, B, and C) based on the expression pattern of cuproptosis regulator genes. The patients in Cu-cluster B had poor prognosis (log-rank test p < 0.001), high genomic instability, and were not sensitive to conventional chemotherapeutic treatment compared to the patients in the other subtypes. Cancer cells in Cu-cluster B exhibited a higher degree of the senescence-associated secretory phenotype (SASP), a marker of cellular senescence. Three representative genes, CDCA8, MCM6, and NCAPG2, were identified in patients in Cu-cluster B using WGCNA and the "randomForest" algorithm. A nomogram was constructed to screen patients in the Cu-cluster B subtype based on three genes: CDCA8, MCM6, and NCAPG2. Publicly available databases and various bioinformatics tools were used to study the heterogeneity of cuproptosis in patients with HCC. Three HCC subtypes were identified, with differences in the survival outcomes, genomic instability, senescence environment, and response to anticancer drugs. Further, three cuproptosis-related genes were identified, which could be used to design personalized therapeutic strategies for HCC.

Loss of hepatic FTCD promotes lipid accumulation and hepatocarcinogenesis by upregulating PPARγ and SREBP2

Exploiting key regulators responsible for hepatocarcinogenesis is of great importance for the prevention and treatment of hepatocellular carcinoma (HCC). However, the key players contributing to hepatocarcinogenesis remain poorly understood. We explored the molecular mechanisms underlying the carcinogenesis and progression of HCC for the development of potential new therapeutic targets. The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and Genotype-Tissue Expression (GTEx) databases were used to identify genes with enhanced expression in the liver associated with HCC progression. A murine liver-specific Ftcd knockout (Ftcd-LKO) model was generated to investigate the role of formimidoyltransferase cyclodeaminase (FTCD) in HCC. Multi-omics analysis of transcriptomics, metabolomics, and proteomics data were applied to further analyse the molecular effects of FTCD expression on hepatocarcinogenesis. Functional and biochemical studies were performed to determine the significance of loss of FTCD expression and the therapeutic potential of Akt inhibitors in FTCD-deficient cancer cells. FTCD is highly expressed in the liver but significantly downregulated in HCC. Patients with HCC and low levels of FTCD exhibited worse prognosis, and patients with liver cirrhosis and low FTCD levels exhibited a notable higher probability of developing HCC. Hepatocyte-specific knockout of FTCD promoted both chronic diethylnitrosamine-induced and spontaneous hepatocarcinogenesis in mice. Multi-omics analysis showed that loss of FTCD affected fatty acid and cholesterol metabolism in hepatocarcinogenesis. Mechanistically, loss of FTCD upregulated peroxisome proliferator-activated receptor (PPAR)γ and sterol regulatory element-binding protein 2 (SREBP2) by regulating the PTEN/Akt/mTOR signalling axis, leading to lipid accumulation and hepatocarcinogenesis. Taken together, we identified a FTCD-regulated lipid metabolic mechanism involving PPARγ and SREBP2 signaling in hepatocarcinogenesis and provide a rationale for therapeutically targeting of HCC driven by downregulation of FTCD. Exploiting key molecules responsible for hepatocarcinogenesis is significant for the prevention and treatment of HCC. Herein, we identified formimidoyltransferase cyclodeaminase (FTCD) as the top enhanced gene, which could serve as a predictive and prognostic marker for patients with HCC. We generated and characterised the first Ftcd liver-specific knockout murine model. We found loss of FTCD expression upregulated peroxisome proliferator-activated receptor (PPAR)γ and sterol regulatory element-binding protein 2 (SREBP2) by regulating the PTEN/Akt/mTOR signalling axis, leading to lipid accumulation and hepatocarcinogenesis, and provided a rationale for therapeutic targeting of HCC driven by downregulation of FTCD.

Curcumin inhibits proliferation of hepatocellular carcinoma cells by blocking PTPN1 and PTPN11 expression.

The antitumor mechanism of curcumin is unclear, especially in hepatocellular carcinoma (HCC) cells. To clarify the mechanism of action of curcumin in the effective treatment of HCC, the targets of curcumin were screened and validated. Candidate genes of curcumin for HCC were screened using the traditional Chinese medicine systems pharmacology (TCMSP) database and validated using The Cancer Genome Atlas (TCGA) database. The correlation of mRNA expression levels between key candidate genes was identified in the TCGA liver hepatocellular carcinoma (LIHC) dataset. The effects on prognosis were analyzed to identify the target gene of curcumin, which inhibits HCC cell proliferation. Based on the subcutaneous xenograft model of human HCC in nude mice, the expression levels of target proteins were observed using immunohistochemistry. The analysis results of the present study identified the target genes of curcumin, which were obtained by screening the TCSMP database. The protein tyrosine phosphatase non-receptor type 1 (PTPN1) was obtained from TCGA database analysis of the targeted genes. The expression levels of PTPN1 and its homologous sequence genes in TCGA LIHC project was analyzed to identify the potential target gene of curcumin, for use in HCC treatment. Next, xenograft experiments were performed to investigate the therapeutic effects of curcumin in an animal model. Curcumin was demonstrated to inhibit the growth of HCC xenograft tumors in mice. Immunohistochemistry results demonstrated that the protein expression levels of PTPN1 and PTPN11 in the curcumin group were significantly lower compared with those in the control group. In conclusion, these results demonstrated that curcumin inhibits the proliferation of HCC cells by inhibiting the expression of PTPN1 and PTPN11.

High expression of RNF31 is associated with tumor immune cell infiltration and leads to poor prognosis in liver hepatocellular carcinoma

Ring finger protein 31 (RNF31) has been found to play an important role in tumor immunity. However, the role of RNF31 in liver hepatocellular carcinoma (LIHC) has not been reported. Therefore, we investigated the expression and prognostic value of RNF31 in patients with LIHC and explored its relationship with immune cell infiltration. The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) dataset was downloaded to analyse the impact of RNF31 on the prognosis and immune cell infiltration of LIHC. The Tumor Immune Estimation Resource (TIMER) database was used to analyse the correlation between RNF31 and tumor immune cell infiltration in LIHC. Additionally, we analysed the relationship between RNF31 and tumor necrosis factor (TNF) as well as the interferon-gamma (IFN-γ) signaling pathway. The expression of RNF31 in LIHC was significantly higher than that in normal tissues. Increased RNF31 expression was associated with decreased overall survival (OS) and relapse-free survival (RFS). An increase in RNF31 expression was closely related to the infiltration levels of immune cells (e.g., natural killer (NK) cells, CD8 + T cells, and B cells). RNF31 was also positively correlated with the expression of immune checkpoint genes in LIHC. Moreover, RNF31 may participate in TNF and IFN-γ signaling pathways. In conclusion, RNF31 is a potentially valuable prognostic biomarker in LIHC. RNF31 is also associated with immune cell infiltration in LIHC. RNF31 may be a potential target for immunotherapy of LIHC.

Combining a machine-learning derived 4-lncRNA signature with AFP and TNM stages in predicting early recurrence of hepatocellular carcinoma

BackgroundNear 70% of hepatocellular carcinoma (HCC) recurrence is early recurrence within 2-year post surgery. Long non-coding RNAs (lncRNAs) are intensively involved in HCC progression and serve as biomarkers for HCC prognosis. The aim of this study is to construct a lncRNA-based signature for predicting HCC early recurrence.MethodsData of RNA expression and associated clinical information were accessed from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database. Recurrence associated differentially expressed lncRNAs (DELncs) were determined by three DEG methods and two survival analyses methods. DELncs involved in the signature were selected by three machine learning methods and multivariate Cox analysis. Additionally, the signature was validated in a cohort of HCC patients from an external source. In order to gain insight into the biological functions of this signature, gene sets enrichment analyses, immune infiltration analyses, as well as immune and drug therapy prediction analyses were conducted.ResultsA 4-lncRNA signature consisting of AC108463.1, AF131217.1, CMB9-22P13.1, TMCC1-AS1 was constructed. Patients in the high-risk group showed significantly higher early recurrence rate compared to those in the low-risk group. Combination of the signature, AFP and TNM further improved the early HCC recurrence predictive performance. Several molecular pathways and gene sets associated with HCC pathogenesis are enriched in the high-risk group. Antitumor immune cells, such as activated B cell, type 1 T helper cell, natural killer cell and effective memory CD8 T cell are enriched in patients with low-risk HCCs. HCC patients in the low- and high-risk group had differential sensitivities to various antitumor drugs. Finally, predictive performance of this signature was validated in an external cohort of patients with HCC.ConclusionCombined with TNM and AFP, the 4-lncRNA signature presents excellent predictability of HCC early recurrence.

Identification of G protein subunit alpha i2 as a promising therapeutic target of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a global health problem. Its incidence and mortality are increasing. Exploring novel therapeutic targets against HCC is important and urgent. We here explored the expression and potential function of Gαi2 (G protein subunit alpha i2) in HCC. The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database shows that the number of Gαi2 transcripts in HCC tissues is significantly higher than that in the normal liver tissues. Moreover, Gαi2 overexpression in HCC correlates with poor prognosis of the patients. Gαi2 mRNA and protein expression are also elevated in local HCC tissues and different human HCC cells. In patient-derived primary HCC cells and immortalized HepG2 cells, Gαi2 silencing (by targeted shRNA) or knockout (KO, by the dCas9-sgRNA method) largely suppressed cell proliferation and motility, while inducing cell cycle arrest and caspase-apoptosis activation. Moreover, Gαi2 silencing or KO-induced reactive oxygen species (ROS) production and oxidative injury in primary and HepG2 HCC cells. Whereas different antioxidants ameliorated Gαi2-shRNA-induced anti-HCC cell activity. Using a lentiviral construct, Gαi2 overexpression further augmented proliferation and motility of primary and immortalized HCC cells. Further studies revealed that the binding between the transcription factor early growth response zinc finger transcription factor 1 (EGR1) and Gαi2 DNA promoter was significantly increased in HCC tissues and cells. In vivo, intratumoral injection of Gαi2 shRNA adeno-associated virus significantly hindered HCC xenograft growth in nude mice. Moreover, the growth of Gαi2-KO HCC xenografts in the nude mice was remarkably slow. Gαi2 depletion, oxidative injury, and apoptosis induction were detected in Gαi2-silenced or Gαi2-KO HCC xenografts. Together, overexpressed Gαi2 is required for HCC cell growth in vitro and in vivo, representing as a novel and promising diagnosis marker and therapeutic target of HCC.

MiR-144-3p represses hepatocellular carcinoma progression by affecting cell aerobic glycolysis via FOXK1.

Aerobic glycolysis is a unique mark of cancer cells, which enables therapeutic intervention in cancer. Forkhead box K1 (FOXK1) is a transcription factor that facilitates the progression of multiple cancers including hepatocellular carcinoma (HCC). Nevertheless, it is unclear whether or not FOXK1 can affect HCC cell glycolysis. This study attempted to study the effect of FOXK1 on HCC cell glycolysis. Expression of mature miRNAs and mRNAs, as well as clinical data, was downloaded from The Cancer Genome Atlas-Liver hepatocellular carcinoma (TCGA-LIHC) dataset. FOXK1 and miR-144-3p levels were assessed through quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Targeting of the relationship between miR-144-3p and FOXK1 was verified via a dual-luciferase assay. Pathway enrichment analysis of FOXK1 was performed by Gene Set Enrichment Analysis (GSEA). Cell function assays revealed the glycolytic ability, cell viability, migration, invasion, cell cycle, and apoptosis of HCC cells in each treatment group. Bioinformatics analysis suggested that FOXK1 was upregulated in tissues of HCC patients, while the upstream miR-144-3p was downregulated in tumour tissues. Dual-luciferase assay implied a targeting relationship between miR-144-3p and FOXK1. Cellular experiments implied that silencing FOXK1 repressed HCC cell glycolysis, which in turn inhibited the HCC malignant progression. Rescue assay confirmed that miR-144-3p repressed glycolysis in HCC cells by targeting FOXK1, and then repressed HCC malignant progression. miR-144-3p/FOXK1 axis repressed malignant progression of HCC via affecting the aerobic glycolytic process of HCC cells. miR-144-3p and FOXK1 have the potential to become new therapeutic targets for HCC, which provide new insights for HCC treatment.

Circadian gene CSNK1D promoted the progression of hepatocellular carcinoma by activating Wnt/β-catenin pathway via stabilizing Dishevelled Segment Polarity Protein 3

PurposeA variety of studies have connected circadian rhythm to the initiation and progression of hepatocellular carcinoma (HCC). The purpose of this study was to figure out about the circadian genes' profile characteristics, prognostic significance, and targeted values in HCC.MethodsThe expression profiles and prognostic significance of circadian genes in the cancer genome atlas liver hepatocellular carcinoma (TCGA-LIHC) database were investigated using bioinformatics analysis. The expression features of Casein Kinase 1 Delta (CSNK1D), a robust signature gene, was further detected by immunohistochemistry, western blotting and Real-time quantitative PCR (RT-qPCR) in a local HCC cohort. The effect of CSNK1D on corresponding phenotypes of HCC cells was evaluated using Cell Counting Kit-8 (CCK8), flowcytometry, clone assay, Transwell assay, and xenograft assay. In addition, the underlying mechanisms of CSNK1D in the Wnt/β-catenin signaling were validated by multiple molecular experiments.ResultsAbnormal expression of the Circadian genome was associated with the malignant clinicopathological characteristics of HCC patients. A 10 circadian gene-based signature with substantial prognostic significance was developed using Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. Of them, CSNK1D, significantly elevated in a local HCC cohort, was chosen for further investigation. Silencing or overexpression of CSNK1D significantly reduced or increased proliferation, invasion, sorafenib resistance, xenograft development, and epithelial-mesenchymal transformation (EMT) of HCC cells, respectively. Mechanically, CSNK1D exacerbated the aggressiveness of HCC cells by activating Wnt/β-catenin signaling through interacting with Dishevelled Segment Polarity Protein 3 (DVL3).ConclusionsThe Circadian gene CSNK1D was found to contribute to HCC progression by boosting the Wnt/β-catenin pathway, hinting that it could be a prospective therapeutic target for HCC.

FAM83D promotes the proliferation and migration of hepatocellular carcinoma cells by inhibiting the FBXW7/MCL1 pathway.

Hepatocellular carcinoma (HCC) is one of the most malignant tumors and has a poor 5-year survival rate. Family with sequence similarity 83, member D (FAM83D) is characterized as an oncogenic gene related to cell proliferation in many tumors, but the role and underlying mechanism of FAM83D in the development of HCC are still unclear. FAM83D expression profiles and clinicopathological data were obtained from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC). Additionally, 2 data sets from the Gene Expression Omnibus (GEO) database were used to further validate the FAM83D profile in HCC. We then downregulated the expression of FAM83D in HCC cells transfected with FAM83D small-interfering ribonucleic acid (siRNA) and upregulating its expression by FAM83D-overexpression transfection for further in vitro studies. TCGA and the GEO databases showed that FAM83D was significantly more upregulated in tumor tissues than non-tumor tissues. The high expression of FAM83D in HCC is associated with poor prognostic clinical factors. The knockdown of FAM83D in SNU449 and HUH7 cells in vitro impaired cell proliferation and migration, and promoted apoptosis, while the overexpression of FAM83D in BEL7402 cells had the opposite effect. Further, combined transfection with FBXW7 siRNA or MCL1-overexpression reversed the role of FAM83D knockdown on cell proliferation, migration, and apoptosis in vitro, while FBXW7 expression was negatively correlated with both the FAM83D and MCL1 levels in TCGA-LIHC patients. FAM83D played a significant role in HCC progression by enhancing cell proliferation and migration and inhibiting apoptosis, which may have been caused by the inhibition of the FBXW7/MCL1 signaling pathway. Thus, FAM83D may be a promising therapeutic target for HCC.