• dual-phenotype
• hepatocellular carcinoma
• overall survival
• prognosis
• recurrence

• National Natural Science Foundation of China
• Zhejiang Provincial Natural Science Foundation of China
• fund of Public Welfare Technology Research Program of Zhejiang Provincial Natural Science Foundation
• General Research Program of Zhejiang Provincial Department of Education
• fund of Medical and Health Research Projects in Zhejiang Province
• Basic Research Funds for Hangzhou Medical College Basic Research Program

• Deep learning
• Hepatocellular carcinoma
• Immune checkpoint inhibitors
• Lenvatinib
• Multiphase computerized tomography

• cancer imaging
• hepatocellular carcinoma
• magnetic resonance tomography
• microvascular invasion
• predictive imaging biomarkers

• Carcinoma, Hepatocellular/pathology
• Carcinoma, Hepatocellular/metabolism
• Humans
• Liver Neoplasms/pathology
• Liver Neoplasms/metabolism
• Animals
• Mice
• Oxygen/metabolism
• Tumor Microenvironment
• Cell Line, Tumor
• Male
• Female
• Xenograft Model Antitumor Assays
• Middle Aged
• Lab-On-A-Chip Devices

• liver
• multi-omics
• steroidal alkaloids
• tomato
• xenobiotic metabolism

• Mice
• Animals
• Solanum lycopersicum
• Xenobiotics/metabolism
• Mice, Inbred C57BL
• Liver/metabolism
• Metabolomics/methods
• Gene Expression Profiling
• Alkaloids/pharmacology
• Steroids/metabolism
• Mammals

• 2014-38420-21844 National Institute of Food and Agriculture
• OHO01405 National Institute of Food and Agriculture
• OHO01470 National Institute of Food and Agriculture
• 3092-51000-061-000 Agricultural Research Service
• 3092-51000-061-002S Agricultural Research Service
• Foods for Health, a focus area of the Discovery Themes at The Ohio State University

• Cuproptosis
• Hepatocellular carcinoma
• Immune infiltration
• Long noncoding RNA
• Prognosis
• Tumor mutation burden

• Humans
• Carcinoma, Hepatocellular/genetics
• RNA, Long Noncoding/genetics
• Liver Neoplasms/genetics
• Prognosis
• Immunity
• Apoptosis

• 2017ZX10203201002-002 National Major Science and Technology Projects of China

• 5-fluorouracil
• genomic variation
• hepatocellular carcinoma
• immune infiltration
• machine learning
• prognosis

• Combination treatment
• Hepatocellular carcinoma
• Magnetic resonance imaging
• Therapeutic response

• cholangiocarcinoma
• hepatocellular carcinoma
• immunoenvironment
• multiplex immunohistochemistry
• tertiary lymphoid structures

Objective: Transcription elongation factor 1 (TCERG1) is a nuclear protein consisted of multiple protein structural domains that plays an important role in regulating the transcription, extension, and splicing regulation of RNA polymerase II. However, the prognostic and immunological role of TCERG1 in human cancer remains unknown. In this study, we analyzed the expression of TCERG1 gene in hepatocellular carcinoma (HCC) patients, its clinical significance, and its possible prognostic value by bioinformatics.

Methods: RNA sequencing data and clinicopathological characteristics of patients with HCC were collected from TCGA and CCLE databases. The Wilcoxon rank-sum test was used to analyze the expression of TCERG1 in HCC tissues and normal tissues. The protein levels of TCERG1 between normal and liver cancer tissues were analyzed by the Human Protein Atlas Database (HPA) (www.proteinatlas.org). Validation was performed using the Gene Expression Omnibus (GEO) dataset of 167 samples. The expression of TCERG1 in HCC cells were verified by qRT-PCR, and CCK-8, scratch assay and Transwell assay were performed to detect cell proliferation, migration and invasion ability. According to the median value of TCERG1 expression, patients were divided into high and low subgroups. Logistic regression, GSEA enrichment, TME, and single-sample set gene enrichment analysis (ssGSEA) were performed to explore the effects of TCERG1 on liver cancer biological function and immune infiltrates. TCERG1 co-expression networks were studied through the CCLE database and the LinkedOmics database to analyze genes that interact with TCERG1.

Results: The expression levels of TCERG1 in HCC patient tissues were significantly higher than in normal tissues. Survival analysis showed that high levels of TCERG1 expression were significantly associated with low survival rates in HCC patients. Multifactorial analysis showed that high TCERG1 expression was an independent risk factor affecting tumor prognosis. This result was also verified in the GEO database. Cellular experiments demonstrated that cell proliferation, migration and invasion were inhibited after silencing of TCERG1 gene expression. Co-expression analysis revealed that CPSF6 and MAML1 expression were positively correlated with TCERG1. GSEA showed that in samples with high TCERG1 expression, relevant signaling pathways associated with cell cycle, apoptosis, pathways in cancer and enriched in known tumors included Wnt signaling pathway, Vegf signaling pathway, Notch signaling pathway, MAPK signaling pathway and MTOR pathways. The expression of TCERG1 was positively correlated with tumor immune infiltrating cells (T helper two cells, T helper cells).

Conclusion:TCERG1 gene is highly expressed in hepatocellular carcinoma tissues, which is associated with the poor prognosis of liver cancer, and may be one of the markers for the diagnosis and screening of liver cancer and the prediction of prognosis effect. At the same time, TCERG1 may also become a new target for tumor immunotherapy.

The heterogeneity of hepatocellular carcinoma (HCC) is related to immune cell infiltration and genetic aberrations in the tumor microenvironment. This study aimed to identify the novel molecular typing of HCC according to the genetic and immune characteristics, to obtain accurate clinical management of this disease. We performed consensus clustering to divide 424 patients into different immune subgroups and assessed the reproducibility and efficiency in two independent cohorts with 921 patients. The associations between molecular typing and molecular, cellular, and clinical characteristics were investigated by a multidimensional bioinformatics approach. Furthermore, we conducted graph structure learning-based dimensionality reduction to depict the immune landscape to reveal the interrelation between the immune and gene systems in molecular typing. We revealed and validated that HCC patients could be segregated into 5 immune subgroups (IS1-5) and 7 gene modules with significantly different molecular, cellular, and clinical characteristics. IS5 had the worst prognosis and lowest enrichment of immune characteristics and was considered the immune cold type. IS4 had the longest overall survival, high immune activity, and antitumorigenesis, which were defined as the immune hot and antitumorigenesis types. In addition, immune landscape analysis further revealed significant intraclass heterogeneity within each IS, and each IS represented distinct clinical, cellular, and molecular characteristics. Our study provided 5 immune subgroups with distinct clinical, cellular, and molecular characteristics of HCC and may have clinical implications for precise therapeutic strategies and facilitate the investigation of immune mechanisms in HCC.

• Carcinoma, Hepatocellular/pathology
• Gene Expression Regulation, Neoplastic
• Humans
• Kaplan-Meier Estimate
• Liver Neoplasms/pathology
• Prognosis
• Reproducibility of Results
• Tumor Microenvironment

• National Key Research and Development Program of China

• Hepatocellular carcinoma
• Magnetic resonance imaging
• Nomogram
• Systemic therapy

Hepatocellular carcinoma (HCC) is the sixth most common tumor worldwide. Additionally, deletion of RAPGEF2 plays a critical role in CNV and related to tumor immune microenvironment, whereas the prognostic potential of RAPGEF2 in HCC patient needs to be explored.

We looked for prognostic potential genes in HCC using a variety of R programs. Then, using the LASSO Cox regression, we thoroughly evaluated and integrated the RAPGEF2-related genes from TCGA database. Meanwhile, utilizing TCGA and ICGA databases, the link between RAPGEF2 and immunotherapy response in HCC was studied. In vivo, the effect of RAPGEF2 on tumor development and the capacity of natural killer (NK) cells to recruit were confirmed. To ascertain the connection between RAPGEF2-related genes and the prognosis of HCC, a prognostic model was created and validated.

We demonstrated RAPGEF2 has a differential expression, and patients with deletion of RAPGEF2 gene get shorter survival in HCC. Additionally, the tissues without RAPGEF2 have a weaker ability to recruit the NK cells and response to immunotherapy. After that, we scoured the database for eight RAPGEF2-related genes linked with a better prognosis in HCC patients. Additionally, silencing RAPGEF2 accelerated tumor development in the HCC mouse model and decreased CD56+ NK cell recruitment in HCC tissues. TCGA database was used to classify patients into low- and high-risk categories based on the expression of related genes. Patients in the low-risk group had a significantly greater overall survival than those in the high-risk group (P < 0.001). Meanwhile, the low-risk group demonstrated connections with the NK cell and immunotherapy response. Finally, the prognostic nomogram showed a high sensitivity and specificity for predicting the survival of HCC patients at 1, 2, and 3 years.

The prognostic model based on RAPGEF2 and RAPGEF2-related genes showed an excellent predictive performance in terms of prognosis and immunotherapy response in HCC, therefore establishing a unique prognostic model for clinical assessment of HCC patients.

Background: Liver hepatocellular carcinoma (LIHC) is a widespread and often deadly neoplasm. There is increasing evidence that necroptosis mediates numerous tumor-associated behaviors, as well as the regulation of the tumor microenvironment, suggesting its use as a biomarker for tumor prognosis.

Methods: Data on mRNA expression and necroptosis regulators were acquired from the TCGA and KEGG databases, respectively. Clinical liver hepatocellular carcinoma (LIHC) patient data and information on the expression of necroptosis regulators were processed by unsupervised cluster analysis was performed on LIHC patients together with necroptotic regulator expression and, differentially expressed necroptosis-related genes (DENRGs) were identified by comparing the two clusters. A signature based on eight DENRGs was constructed and verified through independent data sets, and its relationship with the tumor microenvironment was investigated.

Results: Unsupervised cluster analysis demonstrated inherent immune differences among LIHC patients. In all, 1,516 DENRGs were obtained by comparison between the two clusters. In the training set, the final eight genes obtained by univariate, LASSO, and multivariate Cox regression were utilized for constructing the signature. The survival and receiver operating characteristic (ROC) curve achieved satisfactory results in both sets. The high-risk group was characterized by greater immune infiltration and poor prognosis. The results of survival analysis based on the expression of eight DENRGs further confirmed the signature.

Conclusion: We established and validated a risk signature based on eight DERNGs related to the tumor microenvironment. This provides a possible explanation for the different clinical effects of immunotherapy and provides a novel perspective for predicting tumor prognosis in LIHC.

• Beijing Xisike Clinical Oncology Research Foundation
• Wu Jieping Medical Foundation

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.

• HCC
• O-GlcNAcylation
• SLC35B4
• c-Myc
• nucleotide sugar transporters

• early HCC
• genetic analysis
• hepatocellular carcinoma
• intratumor heterogenerity
• liver cirrhosis
• molecular targeted therapy
• whole-genome sequencing

• HCC
• HSD17B6
• Immune infiltration
• Prognosis
• Therapeutic target
• WGCNA

The present study was designed to prepare Kaempferol loaded nanoparticles (KFP-Np) and evaluate hepatoprotective and antioxidant effects in hepatocellular carcinoma models. KFP was encapsulated with hydroxypropyl methylcellulose acetate succinate (HPMC-AS) and Kollicoat MAE 30 DP polymers to prepare nanoparticles (Nps) by quasi-emulsion solvent diffusion technique (QESD). The prepared Nps were evaluated for different pharmaceutical characterization to select the optimum composition for the in vivo assessment. An animal model of cadmium chloride (CdCl₂)-induced hepatocellular carcinoma in Male Sprague Dawley rats was used in vivo to test the antioxidant and hepatoprotective capacity of free and encapsulated KFP. The prepared Npsshowed nanometric size, low PDI, high drug load as well as encapsulation with a better drug release profile. There was a significant decrease in the increased serum levels of alanine transaminase (ALT), total bilirubin (TBiL), and aspartate transaminase (AST), and the lipid peroxidation’s (MDA) level was attenuated, and levels of markers of the cell antioxidant defence system were restored including Glutathione S-transferase (GST), glutathione (GSH), superoxide dismutase (SOD) and catalase (CAT) via oral pre-treatment with KFP-Np (50 mg/kg b.w. (body weight), 6 weeks). KFP-Np significantly declines an mRNA expression of interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-alpha (TNF-α) as well as decreased nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) protein expression. It also upregulated the mRNA expression and protein expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). While comparing the protective effects of KFP encapsulated in Kollicoat MAE 30 DP and HPMC-AS, Nps was found to be betterthan free KFP. Insummary, result indicate that encapsulation of KFP in NPs provides a potential platform for oxidative stress induce liver injury.

• CdCl2
• Nf-kB
• Nrf2
• hepatoprotective effect
• kaempferol
• kollicoat MAE 30 DP/HPMC-AS nanoparticles

• Drug susceptibility
• Hepatocellular carcinoma cell
• Lipidomics
• Nanostructure-assisted laser desorption/ionization mass spectrometry (NALDI-MS)

Hepatocellular carcinoma (HCC) is an aggressive malignant tumor with a poor prognosis. Reactive oxygen species (ROS) play an important role in tumors; however, the role of ROS-related genes is still unclear in HCC. Therefore, we analyzed the role of ROS-related genes in HCC via bioinformatics methods. Firstly, a prognosis model was constructed using LASSO Cox regression and multivariate analyses. We also investigated the potential function of the ROS-related genes and the correlation with immune infiltration, tumor stemness, and drug sensitivity. ICGC database was used for validation. Secondly, we further analyzed the role of 11 ROS-related genes in HCC. As a member of ROS gene family, the role of STK25 has remained unclear in HCC. We explored the biological function of STK25 using in vitro experiments. The present study was the first to construct a ROS-related prognostic model in HCC. The correlation of ROS-related genes with immune infiltration, tumor stemness, and drug sensitivity was dissected. Furthermore, we demonstrated that STK25 knockdown could increase the proliferation, migration, and invasion capacity of HCC cells.

The incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.

We performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.

We identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171–2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.

As a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

• PRKDC
• early-stage hepatocellular carcinoma (eHCC)
• gene-set signature
• immune cells
• prognosis

• clinical
• liver cancer
• microRNA

• genomic instability
• hepatocellular carcinoma
• immune infiltration
• long non-coding RNA
• prognosis

• Growth rate
• Hepatocellular carcinoma
• SEER
• TNM stage

Liquid 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.

• Oxford Nanopore Technologies
• Thailand
• biomarker
• cell-free DNA
• copy-number variants
• hepatocellular carcinoma
• whole-exome sequencing

Patients with hepatocellular carcinoma (HCC) are usually diagnosed at the later stages and have poor survival outcomes. New molecules are urgently needed for the prognostic predication and individual treatment. Our study showed that high levels of NQO1 expression frequently exist in HCC with an obvious cancer‐specific pattern. Patients with NQO1‐high tumors are significantly associated with poor survival outcomes and serve as independent predictors. Functional experiments showed that NQO1 promotes the growth and aggressiveness of HCC in both in vitro and in vivo models, and the underlying mechanism involved NQO1‐derived amplification of ERK/p38‐NRF2 signaling. Combined block of ERK and NRF2 signaling generated stronger growth inhibition compared with any single block, especially for HCC with high‐NQO1. Therefore, NQO1 is a potential biomarker for HCC early diagnosis and prognosis prediction, and also attractive for cancer‐specific targets for HCC treatment.

• NQO1
• NRF2
• hepatocellular carcinoma
• prognosis
• tumorigenesis

• SPP1
• epigenome
• liver cancer
• stratifin
• systematic integration

• Hedgehog signaling pathway
• Smoothened
• cancer stem cells

DNA methylation is a common chemical modification of DNA in the carcinogenesis of hepatocellular carcinoma (HCC).

In this bioinformatics analysis, 348 liver cancer samples were collected from the Cancer Genome Atlas (TCGA) database to analyse specific DNA methylation sites that affect the prognosis of HCC patients.

10,699 CpG sites (CpGs) that were significantly related to the prognosis of patients were clustered into 7 subgroups, and the samples of each subgroup were significantly different in various clinical pathological data. In addition, by calculating the level of methylation sites in each subgroup, 119 methylation sites (corresponding to 105 genes) were selected as specific methylation sites within the subgroups. Moreover, genes in the corresponding promoter regions in which the above specific methylation sites were located were subjected to signalling pathway enrichment analysis, and it was discovered that these genes were enriched in the biological pathways that were reported to be closely correlated with HCC. Additionally, the transcription factor enrichment analysis revealed that these genes were mainly enriched in the transcription factor KROX. A naive Bayesian classification model was used to construct a prognostic model for HCC, and the training and test data sets were used for independent verification and testing.

This classification method can well reflect the heterogeneity of HCC samples and help to develop personalized treatment and accurately predict the prognosis of patients.

• DNA methylation
• Hepatocellular carcinoma
• Molecular subtype classification
• TCGA database

Chronic liver injury could lead the formation of liver fibrosis, eventually some would develop to hepatocellular carcinoma (HCC), one of the leading malignancies worldwide. The aim of the study is to dissect the role of extracellular signal-regulated kinase 2 (ERK2) signaling in liver fibrosis and inflammation. The choline-deficient, ethionine-supplemented (CDE) diet could lead to fatty livers and generate oval cells, activate hepatocyte stellate cell (HSC) and recruit immune cells as the liver fibrosis model mice. WT and ERK2 deficient (ERK2^−/−) mice were compared in terms of liver weight/body weight, liver function, liver fibrosis markers and the differential gene expression in hepatotoxicity. ERK2^−/− mice display the less degree of liver fibrosis when compared to WT mice. The protein level of alpha smooth muscle (α-SMA) was reduced and several hepatocellular carcinoma-related genes such as MMP9, FoxM1 were down-regulated. In addition, the cell proliferation and the percentages of activated T cells were reduced in ERK2^−/− mice upon liver injury. Therefore, ERK2 plays an important role in regulating liver cirrhosis and inflammation.

• ERK2
• MAPK
• liver cirrhosis
• liver inflammation

• Actins/metabolism
• Animals
• Cell Proliferation
• Forkhead Box Protein M1/metabolism
• Liver Cirrhosis/genetics
• Liver Cirrhosis/metabolism
• Liver Cirrhosis/pathology
• Lymphocyte Activation
• Matrix Metalloproteinase 9/metabolism
• Mice
• Mitogen-Activated Protein Kinase 1/genetics
• Mutation
• T-Lymphocytes/immunology

The complex and heterogeneous nature of hepatocellular carcinoma (HCC) hampers the identification of effective therapeutic strategies. Cancer stem cells (CSCs) represent a fraction of cells within tumors with the ability to self-renew and differentiate, and thus significantly contribute to the formation and maintenance of heterogeneous tumor mass. Increasing evidence indicates high plasticity in tumor cells, suggesting that non-CSCs could acquire stem cell properties through de-differentiation or reprogramming processes. In this paper, we reveal KLF4 as a transcription factor that can induce a CSC-like phenotype in non-CSCs through upregulating the EpCAM and E-CAD expression. Our studies indicated that KLF4 could directly bind to the promoter of EpCAM and increase the number of EpCAM⁺/CD133⁺ liver cancer stem cells (LCSCs) in the HuH7 HCC cell line. When KLF4 was overexpressed in EpCAM⁻/CD133⁻ non-stem cells, the expressions of hepatic stem/progenitor cell genes such as CK19, EpCAM and LGR5 were significantly increased. KLF4 overexpressing non-stem cells exhibited greater cell viability upon sorafenib treatment, while the cell migration and invasion capabilities of these cells were suppressed. Importantly, we detected an increased membranous expression and colocalization of β-CAT, E-CAD and EpCAM in the KLF4-overexpressing EpCAM⁻/CD133⁻ non-stem cells, suggesting that this complex might be required for the cancer stem cell phenotype. Moreover, our in vivo xenograft studies demonstrated that with a KLF4 overexpression, EpCAM⁻/CD133⁻ non-stem cells attained an in vivo tumor forming ability comparable to EpCAM⁺/CD133⁺ LCSCs, and the tumor specimens from KLF4-overexpressing xenografts had increased levels of both the KLF4 and EpCAM proteins. Additionally, we identified a correlation between the KLF4 and EpCAM protein expressions in human HCC tissues independent of the tumor stage and differentiation status. Collectively, our data suggest a novel function for KLF4 in modulating the de-differentiation of tumor cells and the induction of EpCAM⁺/CD133⁺ LCSCs in HuH7 HCC cells.

• EpCAM
• KLF4
• hepatocellular carcinoma (HCC)
• liver cancer stem cells
• reprogramming
• tumor plasticity

• HGF
• Hepatocellular carcinoma
• Lenvatinib
• Resistance
• c-MET

• Antineoplastic Agents/pharmacology
• Apoptosis/drug effects
• Carcinoma, Hepatocellular/drug therapy
• Carcinoma, Hepatocellular/metabolism
• Carcinoma, Hepatocellular/pathology
• Cell Line, Tumor
• Cell Proliferation/drug effects
• Drug Resistance, Neoplasm
• Epithelial-Mesenchymal Transition/drug effects
• Hepatocyte Growth Factor/metabolism
• Hepatocyte Growth Factor/pharmacology
• Humans
• Indoles/pharmacology
• Liver Neoplasms/drug therapy
• Liver Neoplasms/metabolism
• Liver Neoplasms/pathology
• Phenylurea Compounds/pharmacology
• Protein Kinase Inhibitors/pharmacology
• Proto-Oncogene Proteins c-met/antagonists & inhibitors
• Proto-Oncogene Proteins c-met/genetics
• Proto-Oncogene Proteins c-met/metabolism
• Quinolines/pharmacology
• Signal Transduction/drug effects
• Sulfones/pharmacology

To evaluate the difference between hepatitis B virus related hepatocellular carcinoma (HBV-HCC) and non-HBV non-HCV hepatocellular carcinoma (NBNC-HCC) patients based on clinical features and prognosis.

A total of 175 patients with HCC were enrolled. Patients’ characteristics were extracted from medical records. Among them, 107 patients were positive for HBsAg and negative for HCV-Ab while 68 patients were negative for HBsAg and HCV-Ab.

The patients in the NBNC-HCC group were significantly older than those in the HBV-HCC group (P = 0.045). Moreover, vascular invasion was found in 23.4% of HBV-HCC patients, which was significantly higher than that in the NBNC-HCC patients with 10.3% (P = 0.029). Kaplan-Meier analysis revealed that HBV-HCC patients had significantly worse outcomes in terms of overall survival (P = 0.036). Compared with the NBNC-HCC patients, the HBV-HCC patients had a significantly worse disease-free survival (P = 0.0018). The multivariate analysis results indicated that TNM stage (HR = 1.541, 95%CI 1.072–2.412, P = 0.002) and HBV infection (HR = 1.087, 95%CI 1.012–1.655, P = 0.042) were independent risk variables for overall survival. While vascular invasion (HR = 1.562, 95%CI 1.013–2.815, P = 0.042) and HBV infection (HR = 1.650, 95%CI 1.017–2.676, P = 0.037) were independent risk factors associated with disease-free survival.

Our data revealed that HBV-HCC is more common in young males with vascular invasion, while NBNC-HCC occurs mostly in elderly patients, and overall survival rate is significantly better than that of HBV-HCC. Our study therefore provides evidence that patients with HBV-HCC require closer follow-up due to their poor prognosis.

• Biomarker
• Hepatitis B virus
• Hepatocellular carcinoma
• Prognosis

• MCC algorithm
• PPI network
• gene expression profile
• hepatocellular carcinoma
• hub gene

In this study, we established the inflammatory factor grade system (IFGs) based on the hepatocellular carcinoma (HCC) microenvironment to investigate the role of inflammatory factor grade (IFG) in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage I-II.

We enrolled 87 HCC patients with AJCC stage I-II who underwent R0 resection between 2000 and 2012 and had paraffin-embedded specimens. Immunohistochemistry (IHC) was performed to investigate the expression of 12 inflammatory factors and then to establish the IFGs (grade A or B) based on the IHC data. Subsequently, Kaplan-Meier and Cox univariate/multivariate survival analyses were performed to examine the potential prognostic significance.

Higher IFG (IFG-B) is significantly associated with greater tumor size (P=0.037), and IFG-B predicts a worse disease-free survival (DFS, P<0.001). Moreover, a platelet count (PLT) ≤100×10⁹/L, tumor size ≥5 cm, poor tumor differentiation, and IFG-B are independent risk factors for DFS.

Overall, by establishing a grading system for the level of inflammatory factors in the HCC microenvironment, IFG-B can effectively predict poor DFS in AJCC stage I-II HCC patients after R0 resection.

• hepatocellular carcinoma
• inflammation
• prognosis
• recurrence

• electron microscopy
• hepatocellular carcinoma
• lithium carbonate
• ultrastructural organization

Hepatocellular carcinoma (HCC) is the sixth most lethal neoplasm worldwide. Traditional biomarkers often exploit the relationship between a certain gene and cancer progression, but they cannot predict patient survival or prognosis accurately. We aim to construct a new DNA repair-related gene signature that combines several genes to improve prognosis prediction in HCC.

We selected an HCC mRNA sequencing (mRNA-seq) dataset (n=365) from The Cancer Genome Atlas (TCGA), and gene set enrichment analysis (GSEA) was used to explore bioinformatics information and further screen genes. We then built a gene signature based on the Cox proportional hazards regression model.

GSEA revealed that the hallmark DNA repair gene set was significantly upregulated in the tumor phenotype. A set of seven genes, namely, ADA, FEN1, POLR2G, SAC3D1, SEC61A1, SF3A3, and UPF3B, were significantly a ssociated with overall survival (OS) and used to form a gene signature. The signature risk score was calculated and used to divide patients into high‐ and low‐risk groups. The high-risk group showed worse prognosis (log-rank test p<0.0001). Univariate and multivariate Cox regression analysis showed that the prognostic performance of this risk score signature was robust in different subgroups based on clinicopathological features, with p-values <0.05 (HR=2.38, 95% CI (confidence interval) =1.355–4.184), indicating that it can serve as an independent prognostic indicator.

We developed and identified a seven‐gene signature related to the DNA repair process that can predict survival in HCC. It can be used as an effective classification tool and to guide clinical treatment.

• DNA repair
• hepatocellular carcinoma
• mRNAs
• prognostic
• survival

• Cancer stem cell
• Hepatocellular carcinoma
• Sphere-forming assay
• Stearoyl-CoA desaturase 1

• Animals
• Carcinoma, Hepatocellular/metabolism
• Carcinoma, Hepatocellular/pathology
• Cell Line, Tumor
• Cell Proliferation
• Cell Self Renewal
• Drug Resistance, Neoplasm
• Gene Expression Regulation, Neoplastic
• Humans
• Liver Neoplasms/metabolism
• Liver Neoplasms/pathology
• Mice
• Mice, SCID
• Molecular Targeted Therapy
• Neoplastic Stem Cells/pathology
• PPAR alpha/metabolism
• Signal Transduction
• Spheroids, Cellular/pathology
• Stearoyl-CoA Desaturase/genetics
• Stearoyl-CoA Desaturase/metabolism
• Xenograft Model Antitumor Assays

• R01 AA020401 NIAAA NIH HHS
• Major Research Plan
• Shanghai Municipal Population and Family Planning Commission (CN)
• Shanghai Association for Science and Technology
• the Strategic Priority Research Program of the Chinese Academy of Sciences
• National Key Research and Development Program of China
• National High Technology Research and Development Program (863 Program) of China
• Specialized Research Fund for the Doctoral Program of Higher Education and Research Grants Council Earmarked Research Grants Joint Research Scheme
• Projects from Shanghai Science and Technology Commission
• Projects from Shanghai Science and Technology Commission
• The Strategic Priority Research Program of the Chinese Academy of Science
• Young Scientists Fund
• the Sailing Program from the Shanghai and Technology Commission

• APE1
• eigengene
• gene expression
• hepatocellular carcinoma
• liver tumor
• mouse model