A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients

SORBS2, mediated by MEF2D, suppresses the metastasis of human hepatocellular carcinoma by inhibitiing the c-Abl-ERK signaling pathway

The RBP sorbin and SH3 domain-containing 2 (SORBS2) has been reported to be a tumor suppressor and is dysregulated in several cancer types. Nonetheless, the exact function and mechanism of action of SORBS2 in hepatocellular carcinoma (HCC) remain unclear. In this study, we found that expression levels of SORBS2 were significantly lower in HCC tissues than that in normal tissue samples, and underexpression of SORBS2 was associated with lower overall survival tates of patients with HCC. In HCC cell lines, SORBS2 overexpression inhibited cell migration, invasion, and epithelial-mesenchymal transition, whereas SORBS2 inhibition yielded the opposite results. In vivo metastasis assays confirmed that overexpression of SORBS2 markedly inhibited HCC metastasis. Mechanistically, SORBS2 exerted tumor-suppressive effects on HCC by inhibiting the c-Abl/ERK signaling pathway. Furthermore, MEF2D, which binds to the promoter of SORBS2, was identified as an upstream regulator of SORBS2 and reduced SORBS2 expression. Our data suggest that SORBS2, downregulated by MEF2D, suppresses HCC metastasis through the c-Abl/ERK signaling pathway and has the potential to serve as a novel prognostic marker or therapeutic target in HCC.

Prognostic value and prospective molecular mechanism of miR-100-5p in hepatocellular carcinoma: A comprehensive study based on 1,258 samples

The prognostic value and molecular mechanism of microRNA-100-5p (miR-100-5p) in hepatocellular carcinoma (HCC) are still unclear. To explore the prognostic value and the mechanism of miR-100-5p in HCC, the present study analyzed the results of 18 previous studies and bioinformatic datasets. The clinical significance of miR-100-5p and its targets in HCC were investigated using The Cancer Genome Atlas and the Gene Expression Omnibus, as well as relevant literature. In total, 12 online tools were used to predict the target genes of miR-100-5p. Bioinformatics analysis and Spearman correlation analysis were performed, and genomic alterations of the hub genes were evaluated. A meta-analysis with 1,258 samples revealed that miR-100-5p was significantly downregulated in HCC [standard mean difference (SMD), -0.94; 95% confidence interval (CI), -1.14 to -0.74; I2, 35.2%]. Lower miR-100-5p expression was associated with poorer clinical characteristics and a poorer prognosis for patients with HCC. Additionally, bioinformatics analysis revealed that the 'regulation of transcription', 'chromatin remodeling complex', 'transcription regulator activity', 'pathways in cancer' and 'heparan sulfate biosynthesis' were the most enriched terms. Furthermore, expression of histone deacetylase (HDAC)2, HDAC3, SHC-transforming protein 1 (SHC1), Ras-related protein Rac1 (RAC1) and E3 ubiquitin-protein ligase CBL (CBL) was negatively correlated with miR-100-5p expression. Among these, upregulated HDAC2 [hazard ratio (HR), 1.910; 95% CI, 1.309-2.787; P=0.0007], HDAC3 (HR, 1.474; 95% CI, 1.012-2.146; P=0.0435), SHC1 (HR, 1.52; 95% CI, 1.043-2.215; P=0.0281) and RAC1 (HR, 1.817; 95% CI, 1.248-2.645; P=0.0022) were associated with shorter survival. Alterations in HDAC2, SHC1, RAC1 and IGF1R were linked with a poorer outcome for HCC, and alternative splicing of SHC and RAC1 were significantly decreased and increased in HCC, respectively. In summary, the downregulation of miR-100-5p may be involved in the progression and prognosis of HCC. The upregulation of HDAC2, HDAC3, SHC1 and RAC1 may indicate a poorer survival rate for patients with HCC. Thus, miR-100-5p and these 4 potential target genes may provide novel therapeutic targets and prognostic predictors for patients with HCC.

Overexpressing CCT6A Contributes To Cancer Cell Growth By Affecting The G1-To-S Phase Transition And Predicts A Negative Prognosis In Hepatocellular Carcinoma

Purpose

To determine the oncogenic role of the sixth subunit of chaperonin-containing tailless complex polypeptide 1 (CCT6A) in hepatocellular carcinoma (HCC) and address the correlation of CCT6A with clinicopathological characteristics and survival. Additionally, this study aimed to explore the effect of CCT6A on HCC cells and the underlying mechanisms.

Methods

We searched for levels of CCT6A expression in the Oncomine database and GEPIA database, which was then validated by analyzing cancer and adjacent non-cancerous tissues of HCC patients using quantitative PCR, Western blot, and immunohistochemistry assays. The relationship between CCT6A expression and survival was analyzed from the GEPIA database and confirmed by immunohistochemistry assays of 133 HCC tissue sections. In addition, the effect of depleting CCT6A on cell proliferation was assessed by CCK-8 and colony formation assays. Cell cycle analysis, immunofluorescence assays, GSEA analysis, and cyclin D expression analyzed by Western blot were used to explore the possible underlying mechanism how dysregulated CCT6A affect the proliferation of HCC.

Results

Both mRNA and protein levels of CCT6A were increased in HCC tissues. Higher CCT6A expression was significantly associated with reduced overall survival (P = 0.023). CCT6A depletion inhibited cell proliferation and downregulated cyclin D, hindering the G1-to-S phase arrest.

Conclusion

CCT6A may contribute to HCC cell proliferation by accelerating the G1-to-S transition, as it maintains the expression of cyclin D. CCT6A could be considered an oncogene of HCC and could be used as a prognostic biomarker for HCC.

Karyopherin α2-dependent import of E2F1 and TFDP1 maintains protumorigenic stathmin expression in liver cancer

Background

Members of the karyopherin superfamily serve as nuclear transport receptors/adaptor proteins and provide exchange of macromolecules between the nucleo- and cytoplasm. Emerging evidence suggests a subset of karyopherins to be dysregulated in hepatocarcinogenesis including karyopherin-α2 (KPNA2). However, the functional and regulatory role of KPNA2 in liver cancer remains incompletely understood.

Methods

Quantitative proteomics (LC-MS/MS, ~ 1750 proteins in total) was used to study changes in global protein abundance upon siRNA-mediated KPNA2 knockdown in HCC cells. Functional and mechanistic analyses included colony formation and 2D migration assays, co-immunoprecipitation (CoIP), chromatin immunoprecipitation (ChIP), qRT-PCR, immmunblotting, and subcellular fractionation. In vitro results were correlated with data derived from a murine HCC model and HCC patient samples (3 cohorts, n > 600 in total).

Results

The proteomic approach revealed the pro-tumorigenic, microtubule (MT) interacting protein stathmin (STMN1) among the most downregulated proteins upon KPNA2 depletion in HCC cells. We further observed that KPNA2 knockdown leads to reduced tumor cell migration and colony formation of HCC cells, which could be phenocopied by direct knockdown of stathmin. As the underlying regulatory mechanism, we uncovered E2F1 and TFDP1 as transport substrates of KPNA2 being retained in the cytoplasm upon KPNA2 ablation, thereby resulting in reduced STMN1 expression. Finally, murine and human HCC data indicate significant correlations of STMN1 expression with E2F1/TFPD1 and with KPNA2 expression and their association with poor prognosis in HCC patients.

Conclusion

Our data suggest that KPNA2 regulates STMN1 by import of E2F1/TFDP1 and thereby provide a novel link between nuclear transport and MT-interacting proteins in HCC with functional and prognostic significance.

Bioinformatics analysis reveals 6 key biomarkers associated with non-small-cell lung cancer

Objective

Non-small-cell lung cancer (NSCLC) accounts for >85% of lung cancers, and its incidence is increasing. We explored expression differences between NSCLC and normal cells and predicted potential target sites for detection and diagnosis of NSCLC.

Methods

Three microarray datasets from the Gene Expression Omnibus database were analyzed using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted. Then, the String database, Cytoscape, and MCODE plug-in were used to construct a protein–protein interaction (PPI) network and screen hub genes. Overall and disease-free survival of hub genes were analyzed using Kaplan-Meier curves, and the relationship between expression patterns of target genes and tumor grades were analyzed and validated. Gene set enrichment analysis and receiver operating characteristic curves were used to verify enrichment pathways and diagnostic performance of hub genes.

Results

In total, 293 differentially expressed genes were identified and mainly enriched in cell cycle, ECM–receptor interaction, and malaria. In the PPI network, 36 hub genes were identified, of which 6 were found to play significant roles in carcinogenesis of NSCLC: CDC20, ECT2, KIF20A, MKI67, TPX2, and TYMS.

Conclusion

The identified target genes can be used as biomarkers for the detection and diagnosis of NSCLC.

Loss of alanine-glyoxylate and serine-pyruvate aminotransferase expression accelerated the progression of hepatocellular carcinoma and predicted poor prognosis

BACKGROUND

Accumulated studies reported abnormal gene expression profiles of hepatocellular carcinoma (HCC) by cDNA microarray. We tried to merge cDNA microarray data from different studies to search for stably changed genes, and to find out better diagnostic and prognostic markers for HCC.

METHODS

A systematic review was performed by searching publications indexed in Pubmed from March 1, 2001 to July 1, 2016. Studies that reporting cDNA microarray profiles in HCC, containing both tumor and nontumor data and published in English-language were retrieved. The differentially expressed genes from eligible studies were summarized and ranked according to the frequency. High frequency genes were subjected to survival analyses. The expression and prognostic value of alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT) was further evaluated in HCC datasets in Oncomine and an independent HCC tissue array cohort. The role of AGXT in HCC progression was evaluated by proliferation and migration assays in a human HCC cell line.

RESULTS

A total of 43 eligible studies that containing 1917 HCC patients were included, a list of 2022 non redundant abnormally expressed genes in HCC were extracted. The frequencies of reported genes were ranked. We finally obtained a list of only five genes (AGXT; ALDOB; CYP2E1; IGFBP3; TOP2A) that were differentially expressed in tumor and nontumor tissues across studies and were significantly correlated to HCC prognosis. Only AGXT had not been reported in HCC. Reduced expression of AGXT reflected poor differentiation of HCC and predicts poor survival. Knocking down of AGXT enhanced cell proliferation and migration of HCC cell line.

CONCLUSIONS

The present study supported the feasibility and necessity of systematic review on discovering new and reliable biomarkers for HCC. We also identified a list of high frequency prognostic genes and emphasized a critical role of AGXT deletion during HCC progression.

Comprehensive characterization of tumor infiltrating natural killer cells and clinical significance in hepatocellular carcinoma based on gene expression profiles

Natural Killer (NK) cells are effector lymphocytes involved in tumor immunosurveillance, however, the specific mechanism in hepatocellular carcinoma (HCC) has not been well understood. In the present study, we estimated the relative abundances of NK cells in HCC using gene expression data, and found that NK cell abundance was lower in HCC tissues than in the adjacent normal tissues. With the common HCC subclasses, we also found that three HCC subclasses had distinct abundances of NK cells. Moreover, we also found strong association between NK cell abundances and genes encoding immune checkpoint proteins, such as KLRD1, CD96, TIGIT, CD86, HAVCR2, PDCD1 (PD-1), HLA-E, CD274 (PD-L1), and CTLA4, among which, KLRD1 vs. HLA-E, CD274 vs. PDCD1, and CTLA4 vs. CD86 were three pairs of receptors and ligands. Furthermore, we investigated the clinical significance of NK cell activities in HCC, and found that the NK cell abundances were highly associated with the response to sorafinib, and higher NK cell abundances may prolong both the recurrence-free and overall survival of HCC patients. In summary, the present study not only improved our understanding of the potential tumor immune evasion mechanism of NK cells in HCC, but also proposed the potential clinical application of NK activities in HCC treatment and risk assessment.

Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P < 0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.

Functional Genomic Complexity Defines Intratumor Heterogeneity and Tumor Aggressiveness in Liver Cancer

Chronic inflammation and chromosome aneuploidy are major traits of primary liver cancer (PLC), which represent the second most common cause of cancer-related death worldwide. Increased cancer fitness and aggressiveness of PLC may be achieved by enhancing tumoral genomic complexity that alters tumor biology. Here, we developed a scoring method, namely functional genomic complexity (FGC), to determine the degree of molecular heterogeneity among 580 liver tumors with diverse ethnicities and etiologies by assessing integrated genomic and transcriptomic data. We found that tumors with higher FGC scores are associated with chromosome instability and TP53 mutations, and a worse prognosis, while tumors with lower FGC scores have elevated infiltrating lymphocytes and a better prognosis. These results indicate that FGC scores may serve as a surrogate to define genomic heterogeneity of PLC linked to chromosomal instability and evasion of immune surveillance. Our findings demonstrate an ability to define genomic heterogeneity and corresponding tumor biology of liver cancer based only on bulk genomic and transcriptomic data. Our data also provide a rationale for applying this approach to survey liver tumor immunity and to stratify patients for immune-based therapy.

Knockdown of Pyruvate Kinase M2 Inhibits Cell Proliferation, Metabolism, and Migration in Renal Cell Carcinoma

Emerging evidence indicates that the activity of pyruvate kinase M2 (PKM2) isoform is crucial for the survival of tumor cells. However, the molecular mechanism underlying the function of PKM2 in renal cancer is undetermined. Here, we reveal the overexpression of PKM2 in the proximal tubule of renal tumor tissues from 70 cases of patients with renal carcinoma. The functional role of PKM2 in human renal cancer cells following small-interfering RNA-mediated PKM2 knockdown, which retarded 786-O cell growth was examined. Targeting PKM2 affected the protein kinase B (AKT)/mechanistic target of the rapamycin 1 (mTOR) pathway, and downregulated the expression of glycolytic enzymes, including lactate dehydrogenase A and glucose transporter-1, and other downstream signaling key proteins. PKM2 knockdown changed glycolytic metabolism, mitochondrial function, adenosine triphosphate (ATP) level, and intracellular metabolite formation and significantly reduced 786-O cell migration and invasion. Acridine orange and monodansylcadaverine staining, immunocytochemistry, and immunoblotting analyses revealed the induction of autophagy in renal cancer cells following PKM2 knockdown. This is the first study to indicate PKM2/AKT/mTOR as an important regulatory axis mediating the changes in the metabolism of renal cancer cells.

The mRNA-binding Protein TTP/ZFP36 in Hepatocarcinogenesis and Hepatocellular Carcinoma

Hepatic lipid deposition and inflammation represent risk factors for hepatocellular carcinoma (HCC). The mRNA-binding protein tristetraprolin (TTP, gene name ZFP36) has been suggested as a tumor suppressor in several malignancies, but it increases insulin resistance. The aim of this study was to elucidate the role of TTP in hepatocarcinogenesis and HCC progression. Employing liver-specific TTP-knockout (lsTtp-KO) mice in the diethylnitrosamine (DEN) hepatocarcinogenesis model, we observed a significantly reduced tumor burden compared to wild-type animals. Upon short-term DEN treatment, modelling early inflammatory processes in hepatocarcinogenesis, lsTtp-KO mice exhibited a reduced monocyte/macrophage ratio as compared to wild-type mice. While short-term DEN strongly induced an abundance of saturated and poly-unsaturated hepatic fatty acids, lsTtp-KO mice did not show these changes. These findings suggested anti-carcinogenic actions of TTP deletion due to effects on inflammation and metabolism. Interestingly, though, investigating effects of TTP on different hallmarks of cancer suggested tumor-suppressing actions: TTP inhibited proliferation, attenuated migration, and slightly increased chemosensitivity. In line with a tumor-suppressing activity, we observed a reduced expression of several oncogenes in TTP-overexpressing cells. Accordingly, ZFP36 expression was downregulated in tumor tissues in three large human data sets. Taken together, this study suggests that hepatocytic TTP promotes hepatocarcinogenesis, while it shows tumor-suppressive actions during hepatic tumor progression.

A new risk score based on twelve hepatocellular carcinoma-specific gene expression can predict the patients' prognosis

A large panel of molecular biomarkers have been identified to predict the prognosis of hepatocellular carcinoma (HCC), yet with limited clinical application due to difficult extrapolation. We here generated a genetic risk score system comprised of 12 HCC-specific genes to better predict the prognosis of HCC patients. Four genomics profiling datasets (GSE5851, GSE28691, GSE15765 and GSE14323) were searched to seek HCC-specific genes by comparisons between cancer samples and normal liver tissues and between different subtypes of hepatic neoplasms. Univariate survival analysis screened HCC-specific genes associated with overall survival (OS) in the training dataset for next-step risk model construction. The prognostic value of the constructed HCC risk score system was then validated in the TCGA dataset. Stratified analysis indicated this scoring system showed better performance in elderly male patients with HBV infection and preoperative lower levels of creatinine, alpha-fetoprotein and platelet and higher level of albumin. Functional annotation of this risk model in high-risk patients revealed that pathways associated with cell cycle, cell migration and inflammation were significantly enriched. In summary, our constructed HCC-specific gene risk model demonstrated robustness and potentiality in predicting the prognosis of HCC patients, especially among elderly male patients with HBV infection and relatively better general conditions.

A genomic-clinical nomogram predicting recurrence-free survival for patients diagnosed with hepatocellular carcinoma

Liver resection surgery is the most commonly used treatment strategy for patients diagnosed with hepatocellular carcinoma (HCC). However, there is still a chance for recurrence in these patients despite the survival benefits of this procedure. This study aimed to explore recurrence-related genes (RRGs) and establish a genomic-clinical nomogram for predicting postoperative recurrence in HCC patients. A total of 123 differently expressed genes and three RRGs (PZP, SPP2, and PRC1) were identified from online databases via Cox regression and LASSO logistic regression analyses and a gene-based risk model containing RRGs was then established. The Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves showed that the model performed well. Finally, a genomic-clinical nomogram incorporating the gene-based risk model, AJCC staging system, and Eastern Cooperative Oncology Group performance status was constructed to predict the 1-, 2-, and 3-year recurrence-free survival rates (RFS) for HCC patients. The C-index, ROC analysis, and decision curve analysis were good indicators of the nomogram’s performance. In conclusion, we identified three reliable RRGs associated with the recurrence of cancer and constructed a nomogram that performed well in predicting RFS for HCC patients. These findings could enrich our understanding of the mechanisms for HCC recurrence, help surgeons predict patients’ prognosis, and promote HCC treatment.

Screening and identification of key biomarkers in prostate cancer using bioinformatics

Prostate cancer (PCa) is the second most common cancer amongst males worldwide. In the current study, microarray datasets GSE3325 and GSE6919 from the Gene Expression Omnibus database were screened to identify candidate genes that are associated with the progression of PCa. A total of 273 differentially expressed genes (DEGs) were identified, which included 173 downregulated genes and 100 upregulated genes, and a protein-protein interaction network was constructed using Search Tool for the Retired of Interacting Genes. The enriched functions and pathways of the identified DEGs included cell adhesion, the negative regulation of cell proliferation, protein binding and focal adhesion. A total of 8 hub genes were identified, of which PDZ binding kinase, Krüppel-like factor 4, collagen type XII α-1 chain, RAP1A and RAP39B were indicated to be associated with the progression and recurrence of PCa. In conclusion, the DEGs and hub genes identified in the present study may aid in determining the molecular mechanisms associated with PCa carcinogenesis and progression.

Expression levels and prognostic values of annexins in liver cancer

Annexins are a superfamily of calcium-dependent phospholipid-binding proteins that are implicated in a wide range of biological processes. The annexin superfamily comprises 13 members in humans (ANXAs), the majority of which are frequently dysregulated in cancer. However, the expression patterns and prognostic values of ANXAs in liver cancer are currently largely unknown. The present study aimed to analyze the expression levels of ANXAs and survival data in patients with liver cancer from the Oncomine, GEPIA, Kaplan-Meier plotter and cBioPortal for Cancer Genomics databases. The results demonstrated that ANXA1, A2, A3, A4 and A5 were upregulated, whereas ANXA10 was downregulated in liver cancer compared with normal liver tissues. The expression of ANXA10 was associated with pathological stage. High expression levels of ANXA2 and A5 were significantly associated with poor overall survival (OS) rate whereas ANXA7 and A10 were associated with increased OS. The prognostic values of ANXAs in liver cancer were determined based on sex and clinical stage, which revealed that ANXA2, A5, A7 and A10 were associated with OS in male, but not in female patients. In addition, the potential biological functions of ANXAs were identified by Gene Ontology functional annotation and Kyoto Encyclopedia of Genes Genomes pathway analysis; the results demonstrated that ANXAs may serve a role in liver cancer through the neuroactive ligand-receptor interaction pathway. In conclusion, the results of the present study suggested that ANXA1, A2, A3, A4, A5 and A10 may be potential therapeutic targets for liver cancer treatment, and that ANXA2, A5, A7 and A10 may be potential prognostic biomarkers of liver cancer.

Histone Deacetylase Expressions in Hepatocellular Carcinoma and Functional Effects of Histone Deacetylase Inhibitors on Liver Cancer Cells In Vitro

Hepatocellular carcinoma (HCC) is a leading cause for deaths worldwide. Histone deacetylase (HDAC) inhibition (HDACi) is emerging as a promising therapeutic strategy. However, most pharmacological HDACi unselectively block different HDAC classes and their molecular mechanisms of action are only incompletely understood. The aim of this study was to systematically analyze expressions of different HDAC classes in HCC cells and tissues and to functionally analyze the effect of the HDACi suberanilohydroxamic acid (SAHA) and trichostatin A (TSA) on the tumorigenicity of HCC cells. The gene expression of all HDAC classes was significantly increased in human HCC cell lines (Hep3B, HepG2, PLC, HuH7) compared to primary human hepatocytes (PHH). The analysis of HCC patient data showed the increased expression of several HDACs in HCC tissues compared to non-tumorous liver. However, there was no unified picture of regulation in three different HCC patient datasets and we observed a strong variation in the gene expression of different HDACs in tumorous as well as non-tumorous liver. Still, there was a strong correlation in the expression of HDAC class IIa (HDAC4, 5, 7, 9) as well as HDAC2 and 8 (class I) and HDAC10 (class IIb) and HDAC11 (class IV) in HCC tissues of individual patients. This might indicate a common mechanism of the regulation of these HDACs in HCC. The Cancer Genome Atlas (TCGA) dataset analysis revealed that HDAC4, HDAC7 and HDAC9 as well as HDAC class I members HDAC1 and HDAC2 is significantly correlated with patient survival. Furthermore, we observed that SAHA and TSA reduced the proliferation, clonogenicity and migratory potential of HCC cells. SAHA but not TSA induced features of senescence in HCC cells. Additionally, HDACi enhanced the efficacy of sorafenib in killing sorafenib-susceptible cells. Moreover, HDACi reestablished sorafenib sensitivity in resistant HCC cells. In summary, HDACs are significantly but differently increased in HCC, which may be exploited to develop more targeted therapeutic approaches. HDACi affect different facets of the tumorigenicity of HCC cells and appears to be a promising therapeutic approach alone or in combination with sorafenib.

NCAPG Promotes The Proliferation Of Hepatocellular Carcinoma Through PI3K/AKT Signaling

Purpose

Studies show that high expression of non-SMC condensin I complex subunit G (NCAPG) is associated with many tumors. In this study, we explore the mechanism by which NCAPG promotes proliferation in hepatocellular carcinoma (HCC).

Patients and methods

Liver cancer and paracancerous tissue specimens of 90 HCC patients were collected, and expression levels of NCAPG in these tissues and cell lines were evaluated by Western blotting and immunohistochemistry. HCC cells were transfected with siRNAs and plasmids, and pathway activators or inhibitors were added. The 5-ethynyl-2ʹ-deoxyuridine (EdU) proliferation assay was used to measure cell proliferation. Flow cytometry was used to evaluate cell apoptosis. Western blot assays were performed as a standard procedure to detect total protein expression. Treated HCC cells were subcutaneously injected into nude mice.

Results

Analysis using the Oncomine database showed that NCAPG was upregulated in HCC and immunohistochemistry and Western blot assays showed it was upregulated in both HCC tissues and HCC cell lines. The overexpression of NCAPG could promote HCC cell proliferation and reduce HCC cell apoptosis. More importantly, RNA-sequencing analysis predicted that NCAPG plays a role in the HCC via PI3K-AKT signaling pathway. The PI3K/AKT/FOXO4 pathway was aberrantly activated, and the expressions of apoptosis-related protein were altered when NCAPG was overexpressed or silenced both in vitro and in vivo. LY294002, a PI3K inhibitor, could eliminate the NCAPG role of promoting HCC cell proliferation and reducing HCC cell apoptosis, while 740Y-P, a PI3K activator, contributed to the opposite effect.

Conclusion

NCAPG functions as an oncogene in HCC and plays a role in promoting cell proliferation and antiapoptosis through activating the PI3K/AKT/FOXO4 pathway.

Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma

The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, n = 257; Gene Expression Omnibus, GEO, n = 170; International Cancer Genome Consortium, ICGC, n = 142) were used in the current study. Five gene expression subtypes (C1-C5) responsible for global immune genes were identified in HCCs at stage I/II. It was found that subtype C4 was associated with upregulation and subtype C5 was associated with downregulation of immune profiles in most metagenes. Immune-correlation analysis of the five subtypes demonstrated that C3 and C4 had higher immune score and better prognostic outcome, as compared with other subtypes. Moreover, the mutation frequencies of TP53, CTNNB1, and AXIN1 had significant difference in the five subgroups. Further, the expression of PDCD1, CD274, PDCD1LG2, CTLA4, CD86, and CD80 was higher in subtype C4 in comparison with the other subtypes. The WGCNA of immune-related genes in the five subtypes revealed that blue and turquoise modules were positively correlated with subtype C4 and were associated with 12 common pathways in the KEGG database. These results were validated in external cohorts from the NCI (National Cancer Institute) cohort (GSE14520) and the ICGC (International Cancer Genome Consortium) cohort. In summary, one immune-enhanced subtype and one immune-decreased subtype having different immune and clinical characteristics may provide guidance for developing novel treatment strategies for immune system malfunction-related cancer.

Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer

Cellular diversity in tumors is a key factor for therapeutic failures and lethal outcomes of solid malignancies. Here, we determined the single-cell transcriptomic landscape of liver cancer biospecimens from 19 patients. We found varying degrees of heterogeneity in malignant cells within and between tumors and diverse landscapes of tumor microenvironment (TME). Strikingly, tumors with higher transcriptomic diversity were associated with patient's worse overall survival. We found a link between hypoxia-dependent vascular endothelial growth factor expression in tumor diversity and TME polarization. Moreover, T cells from higher heterogeneous tumors showed lower cytolytic activities. Consistent results were found using bulk genomic and transcriptomic profiles of 765 liver tumors. Our results offer insight into the diverse ecosystem of liver cancer and its impact on patient prognosis.

CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC. The DEGs of HCC and normal tissues in GSE102079, GSE121248, GSE84402 and GSE60502 were obtained using R language. The GO function analysis and KEGG pathway enrichment analysis of DEGs were carried out using the DAVID database. Then, the protein–protein interaction (PPI) network was constructed using the STRING database. Hub genes were screened using Cytoscape software and verified using the GEPIA, UALCAN, and Oncomine database. We used HPA database to exhibit the differences in protein level of hub genes and used LinkedOmics to reveal the relationship between candidate genes and tumor clinical features. Finally, we obtained transcription factor (TF) of hub genes using NetworkAnalyst online tool. A total of 591 overlapping up-regulated genes were identified. These genes were related to cell cycle, DNA replication, pyrimidine metabolism, and p53 signaling pathway. Additionally, the GEPIA database showed that the CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 were associated with the poor survival of HCC patients. UALCAN, Oncomine, and HPA databases and qRT-PCR confirmed that these genes were highly expressed in HCC tissues. LinkedOmics database indicated these genes were correlated with overall survival, pathologic stage, pathology T stage, race, and the age of onset. TF analysis showed that MYBL2, KDM5B, MYC, SOX2, and E2F4 were regulators to these nine hub genes. Overexpression of CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 in tumor tissues predicted poor survival in HCC. They may be potential therapeutic targets for HCC.

Gene signature predictive of hepatocellular carcinoma patient response to transarterial chemoembolization

Transarterial chemoembolization (TACE) is a commonly used treatment modality in hepatocellular carcinoma (HCC). The ability to identify patients who will respond to TACE represents an important clinical need, and tumor gene expression patterns may be associated with TACE response. We investigated whether tumor transcriptome is associated with TACE response in patients with HCC. We analyzed transcriptome data of treatment-naïve tumor tissues from a Chinese cohort of 191 HCC patients, including 105 patients who underwent TACE following resection with curative intent. We then developed a gene signature, TACE Navigator, which was associated with improved survival in patients that received either adjuvant or post-relapse TACE. To validate our findings, we applied our signature in a blinded manner to three independent cohorts comprising an additional 130 patients with diverse ethnic backgrounds enrolled in three different hospitals who received either adjuvant TACE or palliative TACE. TACE Navigator stratified patients into Responders and Non-Responders which was associated with improved survival following TACE in our test cohort (Responders: 67 months vs Non-Responders: 39.5 months, p<0.0001). In addition, multivariable Cox model demonstrates that TACE Navigator was independently associated with survival (HR: 9.31, 95% CI: 3.46-25.0, p<0.001). In our validation cohorts, the association between TACE Navigator and survival remained robust in both Asian patients who received adjuvant TACE (Hong Kong: 60 months vs 25.6 months p=0.007; Shandong: 61.3 months vs 32.1 months, p=0.027) and European patients who received TACE as primary therapy (Mainz: 60 months vs 41.5 months, p=0.041). These results indicate that a TACE-specific molecular classifier is robust in predicting TACE response. This gene signature can be used to identify patients who will have the greatest survival benefit after TACE treatment and enable personalized treatment modalities for patients with HCC.

Data mining of the expression and regulatory role of BCAT1 in hepatocellular carcinoma

Branched chain amino acid transaminase 1 (BCAT1) catalyzes the production of glutamates and branched-chain α-ketoacids from branched chain amino acids, and a normal BCAT1 expression is associated with tumorigenesis. Sequencing data from public databases, including The Cancer Genome Atlas, was used to analyze BCAT1 expression and regulation networks for hepatocellular carcinoma (HCC). Expression and methylation were assessed using UALCAN analysis, and data from multiple datasets concerning the BCAT1 expression level and associated survival rates were further analyzed using HCCDB; interaction networks of biological function were constructed using GeneMANIA. LinkedOmics was used to indicate correlations between BCAT1 and any identified differentially expressed genes. Gene enrichment analysis of BCAT-associated genes was conducted using the Web-based Gene SeT AnaLysis Toolkit. The expression levels of BCAT1 were increased in patients with HCC and in most cases, the level of BCAT1 promoter methylation was reduced. Interaction network analysis suggested that BCAT1 was involved in ‘metabolism’, ‘carcinogenesis’ and the ‘immune response’ via numerous cancer-associated pathways. The present study revealed the expression patterns and potential function networks of BCAT1 in HCC, providing insights for future research into the role of BCAT1 in hepatocarcinogenesis. In addition, the study provided researchers with a way to analyze the genes of interest so they can continue their research in the right direction.

DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma

In this study, we performed a comprehensively analysis of gene expression and DNA methylation data to establish diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).

Methods: We collected gene expression and DNA methylation datasets for over 1,200 clinical samples. Integrated analyses of RNA-sequencing and DNA methylation data were performed to identify DNA methylation-driven genes. These genes were utilized in univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to build a prognostic model. Recurrence and diagnostic models for HCC were also constructed using the same genes.

Results: A total of 123 DNA methylation-driven genes were identified. Two of these genes (SPP1 and LCAT) were chosen to construct the prognostic model. The high-risk group showed a markedly unfavorable prognosis compared to the low-risk group in both training (HR = 2.81; P < 0.001) and validation (HR = 3.06; P < 0.001) datasets. Multivariate Cox regression analysis indicated the prognostic model to be an independent predictor of prognosis (P < 0.05). Also, the recurrence model successfully distinguished the HCC recurrence rate between the high-risk and low-risk groups in both training (HR = 2.22; P < 0.001) and validation (HR = 2; P < 0.01) datasets. The two diagnostic models provided high accuracy for distinguishing HCC from normal samples and dysplastic nodules in the training and validation datasets, respectively.

Conclusions: We identified and validated prognostic, recurrence, and diagnostic models that were constructed using two DNA methylation-driven genes in HCC. The results obtained by integrating multidimensional genomic data offer novel research directions for HCC biomarkers and new possibilities for individualized treatment of patients with HCC.

High interleukin-8 and/or extracellular signal-regulated kinase 2 expression predicts poor prognosis in patients with hepatocellular carcinoma

Interleukin (IL)-8 and extracellular signal-regulated kinase (ERK) 2 play key roles in tumor progression, but the relationship between IL-8 and/or ERK2 expression in hepatocellular carcinoma (HCC) tissues and postoperative recurrence or survival is unclear. The expression levels of IL-8 and ERK2 in both HCC tissues and non-tumor liver tissues were analyzed using the Oncomine™ database and immunohistochemistry assay. Reverse transcription-quantitative PCR was then used to evaluate the expression levels of IL-8 and ERK2 in the tumor tissues of 67 patients with HCC undergoing radical hepatectomy. Pearson's correlation, Kaplan-Meier, Cox univariate and multivariate survival analyses were utilized to determine the correlation between IL-8 and ERK2 expression in HCC tissues, and their potential prognostic significance. As indicated by the data from the Oncomine™ database, and the patient samples, IL-8 and ERK2 were expressed at significantly higher levels in HCC tissues than in non-tumor liver tissues (P<0.05). The rates of high IL-8 and ERK2 expression in HCC tissues were 43.28 (29/67) and 34.33% (23/67), respectively, and the IL-8 and ERK2 expression levels were positively correlated (r=0.764; P<0.001). Both ERK2 expression and IL-8/ERK2 co-expression were significantly associated with tumor size and differentiation (P<0.05). Additionally, high expression levels of IL-8, ERK2 and IL-8/ERK2 co-expression were all significantly associated with poor overall survival (OS; P<0.05) and disease-free survival (DFS; P<0.05). Multivariate Cox regression analysis also showed that high expression levels of IL-8, ERK2, and IL-8 and ERK2 were independent prognostic factors for OS and DFS (P<0.05). The results of the present study indicate a significant increase in the risk of recurrence and mortality in HCC patients with high expression levels of IL-8 and/or ERK2, compared with patients with low expression. Therefore, IL-8 and ERK2 may be predictors of postoperative prognosis in patients with HCC.

Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma

Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods.

Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification.

Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients.

Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC.

Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.

AKR1C1-3, notably AKR1C3, are distinct biomarkers for liver cancer diagnosis and prognosis: Database mining in malignancies

Aldo-keto reductases, known as AKR1C1-AKR1C4 enzymes, are pivotal to NADPH-dependent reduction, and their expression is highly associated with the progression of malignant cancers. However, the expression and distinct prognostic value of the AKR1C family members in liver cancer are not well established. In the current study, the expression of AKR1C isoforms was studied using the Oncomine online databases. In addition, their expression profiles were analyzed in cancer cell lines using data from the Cancer Cell lines Encyclopedia (CCLE) database. Furthermore, the mRNA expression levels of AKR1C family members between liver cancer and normal liver samples were assessed by the Gene Expression Profiling Interactive Analysis (GEPIA) database. The AKR1C1-3 prognostic value was further investigated by the Kaplan-Meier plotter database in liver cancer patients. It was found that the expression levels of AKR1C3 were elevated significantly in liver cancer tissues and cells as demonstrated by the Oncomine, CCLE and GEPIA databases. The expression levels of AKR1C1 and AKR1C2 in liver cancer tissues did not increase significantly in the Oncomine database while expression was significantly high in CCLE and GEPIA databases. However, the expression levels of the AKR1C4 gene as determined by the CCLE, GEPIA and Oncomine databases were not consistent. Therefore, the Kaplan-Meier survival curves of liver cancer patients with the expression of AKR1C1-3 genes were next analyzed. The data indicated that high expression levels of AKR1C1-3 were correlated with lower overall survival in liver cancer patients. Using the co-expression and PPI network, AKR1C1-3 genes were identified that were involved in the same pathway displaying 44 total unique interactors. These results suggested that the increased AKR1C1-3, notably AKR1C3 expression levels served as possible diagnostic biomarkers and essential prognostic factors for liver cancer patients. The roles of AKR1C4 in liver cancer require further examination.

Tspan15 Is a New Stemness-Related Marker in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the second cause of cancer-related deaths worldwide. A clearer understanding of the molecular mechanisms underlying tumor growth and invasiveness remains crucial for developing new therapies. Here, the expression of tetraspanins, a family of plasma membrane organizers involved in tumor progression, has been addressed. Integrative approaches combining transcriptomics and bioinformatics allow demonstrating the induced and heterogeneous expression of Tspan15 in HCC. Tspan15 positive tumors exhibit signatures related to hepatic progenitor cells as well as recurrence of cancer. Immunohistochemistry experiments confirm Tspan15 expression in the subset of HCC expressing stemness-related markers such as EpCAM and Cytokeratin-19. Functional networks reveal that most of these genes expressed in correlation to Tspan15 support cell proliferation. Furthermore, Tspan15 overexpression in the hepatoma cell line HepG2 significantly increases cell proliferation. A quantitative proteomic analysis of the secretome reveals a higher abundance of the protein connective tissue growth factor (CTGF), a pleiotropic matricellular signaling protein. Proteomic profiling of Tspan15 complexes allows identifying numerous membrane proteins including several growth factor receptors. Finally, Tspan15 increases ERK1/2 phosphorylation that directly controls CTGF expression and secretion. In conclusion, Tspan15 is a new stemness-related marker in HCC which exhibits high potential of tumor growth and recurrence.

Prognostic roles of the transcriptional expression of exportins in hepatocellular carcinoma

Aims: A large number of studies have suggested that exportins (XPOs) play a pivotal role in human cancers. In the present study, we analyzed XPO mRNA expression in cancer tissues and explored their prognostic value in hepatocellular carcinoma (HCC).Methods: Transcriptional and survival data related to XPO expression in HCC patients were obtained through the ONCOMINE and UALCAN databases. Survival analysis plots were drawn with Gene Expression Profiling Interactive Analysis (GEPIA). Sequence alteration data for XPOs were obtained from The Cancer Genome Atlas (TCGA) database and c-BioPortal. Gene functional enrichment analyses were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID).Results: Compared with normal liver tissues, significant XPO mRNA overexpression was observed in HCC cancer tissues. There was a trend of higher XPO expression in more advanced clinical stages and lower differentiated pathological grades of HCC. In HCC patients, high expression of XPO1, CSE1L, XPOT, XPO4/5/6 was related to poor overall survival (OS), and XPO1, CSE1L and XPO5/6 were correlated with poor disease-free survival (DFS). The main genetic alterations in XPOs involved mRNA up-regulation, DNA amplification and deletion. General XPO mutations were remarkably associated with worse OS and mostly affected the pathways of RNA transport and oocyte meiosis.Conclusion: High expression of XPOs was associated with a poor prognosis in HCC patients. XPOs may be exploited as good prognostic biomarkers for survival in HCC patients.

Diagnostic and prognostic biomarkers of Human Leukocyte Antigen complex for hepatitis B virus-related hepatocellular carcinoma

Background: Hepatitis B virus infection had been identified its relationship with liver diseases, including liver tumors. We aimed to explore diagnostic and prognostic values between the Human Leukocyte Antigen (HLA) complex and hepatocellular carcinoma (HCC). Methods: We used the GSE14520 dataset to explore diagnostic and prognostic significance between HLA complex and HCC. A nomogram was constructed to predict survival probability of HCC prognosis. Gene set enrichment analysis was explored using gene ontologies and metabolic pathways. Validation of prognostic values of the HLA complex was performed in the Kaplan-Meier Plotter website. Results: We found that HLA-C showed the diagnostic value (P <0.0001, area under curve: 0.784, sensitivity: 93.14%, specificity: 62.26%). In addition, HLA-DQA1 and HLA-F showed prognostic values for overall survival, and HLA-A, HLA-C, HLA-DPA1 and HLA-DQA1 showed prognostic values for recurrence-free survival (all P ≤ 0.05, elevated 0.927, 0.992, 1.023, 0.918, 0.937 multiples compared to non-tumor tissues, respectively). Gene set enrichment analysis found that they were involved in antigen processing and toll like receptor signalling pathway, etc. The nomogram was evaluated for survival probability of HCC prognosis. Validation analysis indicated that HLA-C, HLA-DPA1, HLA-E, HLA-F and HLA-G were associated with HCC prognosis of overall survival (all P ≤ 0.05, elevated 0.988 and 0.997 multiples compared to non-tumor tissues, respectively). Conclusion: HLA-C might be a diagnostic and prognostic biomarker for HCC. HLA-DPA1 and HLA-F might be prognostic biomarkers for HCC.

RNA-binding protein RPS3 contributes to hepatocarcinogenesis by post-transcriptionally up-regulating SIRT1

Although several studies indicate that RNA-binding proteins (RBPs) contribute to key steps in a variety of physiological processes and cancer, the detailed biological functions and mechanisms remain to be determined. By performing bioinformatics analysis using well-established hepatocellular carcinoma (HCC) datasets, we identified a set of HCC progression-associated RBPs (HPARBPs) and found that the global expression of HPARBPs was significantly correlated with patient prognosis. Among the 42 HPARBPs, human ribosomal protein S3 (RPS3) was one of the most abundant genes whose role remains uncharacterized in HCC. Gain- and loss-of-function analyses demonstrated that RPS3 promoted HCC tumorigenesis both in vitro and in vivo. Mechanistically, we revealed that silent information regulator 1 (SIRT1) was a critical target of RPS3 and was essential for sustaining the RPS3-induced malignant phenotypes of HCC cells. RPS3 stabilized SIRT1 mRNA by binding to AUUUA motifs in the 3448–3530 region of the 3′ untranslated region (UTR) of SIRT1 mRNA. In addition, we found that (5-formylfuran-2-yl) methyl 4-hydroxy-2-methylenebutanoate (FMHM) inhibited HCC progression by repressing the RPS3/SIRT1 pathway. Our study unveils a novel extra-ribosomal role of RPS3 in facilitating hepatocarcinogenesis via the post-transcriptional regulation of SIRT1 expression and proposes that the RPS3/SIRT1 pathway serves as a potential therapeutic target in HCC.

Analysis of clinical significance and prospective molecular mechanism of main elements of the JAK/STAT pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one the most common malignancies and has poor prognosis in patients. The aim of the present study is to explore the clinical significance of the main genes involved in the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway in HCC. GSE14520, a training cohort containing 212 hepatitis B virus-infected HCC patients from the Gene Expression Omnibus database, and data from The Cancer Genome Atlas as a validation cohort containing 370 HCC patients, were used to analyze the diagnostic and prognostic significance for HCC. Joint-effect analyses were performed to determine diagnostic and prognostic significance. Nomograms and risk score models were constructed to predict HCC prognosis using the two cohorts. Additionally, molecular mechanism analysis was performed for the two cohorts. Prognosis-associated genes in the two cohorts were further validated for differential expression using reverse transcription-quantitative polymerase chain reaction of 21 pairs of hepatitis B virus-infected HCC samples. JAK2, TYK2, STAT3, STAT4 and STAT5B had diagnostic significance in the two cohorts (all area under curves >0.5; P≤0.05). In addition, JAK2, STAT5A, STAT6 exhibited prognostic significance in both cohorts (all adjusted P≤0.05). Furthermore, joint-effect analysis had advantages over using one gene alone. Molecular mechanism analyses confirmed that STAT6 was enriched in pathways and terms associated with the cell cycle, cell division and lipid metabolism. Nomograms and risk score models had advantages for HCC prognosis prediction. When validated in 21 pairs of HCC and non-tumor tissue, STAT6 was differentially expressed, whereas JAK2 was not differentially expressed. In conclusion, JAK2, STAT5A and STAT6 may be potential prognostic biomarkers for HCC. JAK2, TYK2, STAT3, STAT4 and STAT5B may be potential diagnostic biomarkers for HCC. STAT6 has a role in HCC that may be mediated via effects on the cell cycle, cell division and lipid metabolism.

Tumor-Infiltrating Leukocyte Composition and Prognostic Power in Hepatitis B- and Hepatitis C-Related Hepatocellular Carcinomas

Background: Tumor-infiltrating leukocytes (TILs) are immune cells surrounding tumor cells, and several studies have shown that TILs are potential survival predictors in different cancers. However, few studies have dissected the differences between hepatitis B- and hepatitis C-related hepatocellular carcinoma (HBV−HCC and HCV−HCC). Therefore, we aimed to determine whether the abundance and composition of TILs are potential predictors for survival outcomes in HCC and which TILs are the most significant predictors. Methods: Two bioinformatics algorithms, ESTIMATE and CIBERSORT, were utilized to analyze the gene expression profiles from 6 datasets, from which the abundance of corresponding TILs was inferred. The ESTIMATE algorithm examined the overall abundance of TILs, whereas the CIBERSORT algorithm reported the relative abundance of 22 different TILs. Both HBV−HCC and HCV−HCC were analyzed. Results: The results indicated that the total abundance of TILs was higher in non-tumor tissue regardless of the HCC type. Alternatively, the specific TILs associated with overall survival (OS) and recurrence-free survival (RFS) varied between subtypes. For example, in HBV−HCC, plasma cells (hazard ratio [HR] = 1.05; 95% CI 1.00–1.10; p = 0.034) and activated dendritic cells (HR = 1.08; 95% CI 1.01–1.17; p = 0.03) were significantly associated with OS, whereas in HCV−HCC, monocytes (HR = 1.21) were significantly associated with OS. Furthermore, for RFS, CD8+ T cells (HR = 0.98) and M0 macrophages (HR = 1.02) were potential biomarkers in HBV−HCC, whereas neutrophils (HR = 1.01) were an independent predictor in HCV−HCC. Lastly, in both HBV−HCC and HCV−HCC, CD8+ T cells (HR = 0.97) and activated dendritic cells (HR = 1.09) had a significant association with OS, while γ delta T cells (HR = 1.04), monocytes (HR = 1.05), M0 macrophages (HR = 1.04), M1 macrophages (HR = 1.02), and activated dendritic cells (HR = 1.15) were highly associated with RFS. Conclusions: These findings demonstrated that TILs are potential survival predictors in HCC and different kinds of TILs are observed according to the virus type. Therefore, further investigations are warranted to elucidate the role of TILs in HCC, which may improve immunotherapy outcomes.

Upregulation of hypoxia-inducible factor 1α mRNA expression was associated with poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

HIF1α mRNA expression in hepatocellular carcinoma (HCC) tissues and its relationship with the prognosis in HCC patients is still unclear. We performed this study to investigate the expression of HIF1α mRNA and its correlation with the prognosis in HCC patients.

MATERIALS AND METHODS

GSE14520 and Oncomine database were used to analyse the differential expression of HIF1α mRNA among HCC tissues and corresponding peritumour tissues or normal liver tissues. The relationship between HIF1α mRNA expression and the clinicopathological features and survival in HCC patients was analysed using the GSE14520 dataset. CCK-8 assay, wound-healing assay, transwell invasion assay, tube formation assay, and subcutaneous xenograft tumour assays using nude mice were used to confirm the function of HIF1α.

RESULTS

Expression of HIF1α mRNA was significantly upregulated in HCC tissues (P<0.05 in all cases); this was supported by the results of the Western blotting (P=0.031) and IHC analyses. Our analysis of the clinicopathological features of HCC patients indicated that high HIF1α mRNA expression was strongly related with TNM stage III (P=0.002) and BCLC stage C (P=0.038). Survival analysis demonstrated that HCC patients with high HIF1α mRNA expression had a short overall survival (OS) (P=0.048), but showed no significant difference in recurrence-free survival (RFS) (P=0.066) compared to patients with low HIF1α mRNA expression. We further demonstrated that HIF1α promoted the proliferation, migration, invasion, and angiogenic ability of HCC cells, by using the stably transformed SK-Hep1 and Hep-3B cell lines showing HIF1α overexpression. Finally, xenograft tumour models of nude mice showed that RNA interference-mediated HIF1α silencing suppressed tumour growth and angiogenesis in HCC.

CONCLUSION

Our study suggests that the upregulation of HIF1α mRNA, which is found in HCC tissues and associated with poor prognosis in HCC patients, contributed to the proliferation, migration, invasion, and angiogenic ability of HCC cells.

CBX3/HP1γ promotes tumor proliferation and predicts poor survival in hepatocellular carcinoma

HP1γ, encoded by CBX3, is associated with cancer progression and patient prognosis. However, the prognostic value and functions of CBX3/HP1γ in hepatocellular carcinoma (HCC) remain unclear. Here, we performed a bioinformatics analysis using the Oncomine, TCGA and Human Protein Atlas databases, the Kaplan-Meier plotter, and the UALCAN web-portal to explore the expression and prognostic significance of CBX3/HP1γ in patients with different cancers, including liver cancer. HCC tissues and microarrays containing 354 samples were examined using immunohistochemical staining, quantitative real-time polymerase chain reaction, and Western blotting. CBX3-overexpression HCC cell lines were tested in proliferation assays to determine the function of CBX3/HP1γ. We found that CBX3/HP1γ was upregulated in many cancers and was associated with poor prognosis. Our results also revealed that CBX3/HP1γ is elevated in HCC tissues and is associated with malignant clinicopathological characteristics. Kaplan-Meier and Cox regression analyses verified that high CBX3/HP1γ expression is an independent and significant prognostic factor for reduced overall survival in HCC patients. Moreover, invitro functional assays showed that CBX3/HP1γ overexpression promotes HCC cell proliferation. These findings suggest that CBX3/HP1γ is an important oncogene in HCC that might act as a useful biomarker for prognosis and targeted therapy.

Expression of GLS1 in intrahepatic cholangiocarcinoma and its clinical significance

Kidney‑type glutaminase (GLS1) plays a significant role in tumor metabolism. Our recent studies demonstrated that GLS1 was aberrantly expressed in hepatocellular carcinoma (HCC) and facilitated tumor progression. However, the roles of GLS1 in intrahepatic cholangiocarcinoma (ICC) remain largely unknown. Thus, the aim of this study was to evaluate the expression and clinical significance of GLS1 in ICC. For this purpose, combined data from the Oncomine database with those of immunohistochemistry were used to determine the expression levels of GLS1 in cancerous and non‑cancerous tissues. Second, a wound‑healing assay and Transwell assay were used to observe the effects of the knockdown and overexpression of GLS1 on the invasion and migration of ICC cells. We examined the associations between the expression of GLS1 and epithelial‑mesenchymal transition (EMT)‑related markers by western blot analysis. Finally, we examined the associations between GLS1 levels and clinicopathological factors or patient prognosis. The results revealed that GLS1 was overexpressed in different digestive system tumors, including ICC, and that GLS1 expression in ICC tissue was higher than that in peritumoral tissue. The overexpression of GLS1 in RBE cells induced metastasis and invasion. Moreover, the EMT‑related markers, E‑cadherin and Vimentin, were regulated by GLS1 in ICC cells. By contrast, the knockdown of GLS1 expression in QBC939 cells yielded opposite results. Clinically, a high expression of GLS1 in ICC samples negatively correlated with E‑cadherin expression and positively correlated with Vimentin expression. GLS1 protein expression was associated with tumor differentiation (P=0.001) and lymphatic metastasis (P=0.029). Importantly, patients with a high GLS1 expression had a poorer overall survival (OS) and a shorter time to recurrence than patients with a low GLS1 expression. Multivariate analysis indicated that GLS1 expression was an independent prognostic indicator. On the whole, the findings of this study demonstrated that GLS1 is an independent prognostic biomarker of ICC. GLS1 facilitates ICC progression and may thus prove to be a therapeutic target in ICC.

The prognostic value of ADRA1 subfamily genes in gastric carcinoma

Adrenergic receptor α1 (ADRA1) subfamily members, including ADRA1A, ADRA1B and ADRA1D, are understood to participate in cardiac disease and benign prostatic hyperplasia. In addition, adrenergic signals in cell pathways can promote the development of cancer. However, little is understood regarding the associations between ADRA1 subfamily members and gastric carcinoma (GC). The present study investigated the prognostic value of the ADRA1 subfamily genes in GC. Data from a total of 379 patients with GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Kaplan-Meier analysis and Cox regression analysis were used to determine associations with overall survival (OS) and to evaluate the median survival time using hazard ratios (HRs) and 95% confidence intervals (CIs). Multivariate survival analysis revealed that low expression levels of ADRA1A (HR, 0.595; 95% CI, 0.426–0.831; adjusted P=0.002) ADRA1B (HR, 0.576; 95% CI, 0.412–0.805; adjusted P=0.001) and ADRA1D (HR, 0.559; 95% CI, 0.398–0.787; adjusted P=0.001) were associated with a favourable OS. Joint-effects analysis demonstrated that combinations of low expression levels of ARDA1A, ARDA1B and ARDA1D were significantly associated with a favourable OS. Overall, the current results suggested that the mRNA expression levels of ARDA1 subfamily members may serve as potential prognostic markers for GC.

Identification of hedgehog signaling as a potential oncogenic driver in an aggressive subclass of human hepatocellular carcinoma: A reanalysis of the TCGA cohort

Hepatocellular carcinoma (HCC) is a heterogeneous disease and the second most common cause of cancer-related death worldwide. Marked developments in genomic technologies helped scientists to understand the heterogeneity of HCC and identified multiple HCC-related molecular subclasses. An integrative analysis of genomic datasets including 196 patients from The Cancer Genome Atlas (TCGA) group has recently reported a new HCC subclass, which contains three subgroups (iCluster1, iCluster2, and iCluster3). However, the transcriptional molecular characteristics underlying the iClusters have not been thoroughly investigated. Herein, we identified a more aggressive subset of HCC patients in the iCluster1, and re-clustered the TCGA samples into novel HCC subclasses referred to as aggressive (Ag), moderate-aggressive (M-Ag), and less-aggressive (L-Ag) subclasses. The Ag subclass had a greater predictive power than the TCGA iCluster1, and a higher level of alpha fetoprotein, microscopic vascular invasion, immune infiltration, isocitrate dehydrogenase 1/2 mutation status, and a worse survival than M-Ag and L-Ag subclasses. Global transcriptomic analysis showed that activation of hedgehog signaling in the Ag subclass may play key roles in tumor development of aggressive HCC. GLI1, a key transcriptional regulator of hedgehog signaling upregulated in the Ag subclass, was correlated with poor prognosis of HCC, and may be a potential prognostic biomarker and therapeutic target for Ag subclass HCC patients.

Roles of organic anion transporter 2 and equilibrative nucleoside transporter 1 in hepatic disposition and antiviral activity of entecavir during non-pregnancy and pregnancy

BACKGROUND AND PURPOSE

Entecavir (ETV), a first-line antiviral drug against hepatitis B virus (HBV), has the possibility to be used to prevent mother-to-child transmission. The aim of present study was to clarify the mechanism of ETV uptake into hepatocytes and evaluate the alteration of ETV's hepatic distribution during pregnancy.

EXPERIMENTAL APPROACH

The roles of equilibrative nucleotide transporter (ENT) 1 and organic anion transporter (OAT) 2 in ETV accumulation and anti-HBV efficacy were studied in human ENT1 or OAT2 overexpressed cell models and HepG2.2.15 cells, respectively; meanwhile, the liver-to-plasma ETV concentration ratios in non-pregnant and pregnant mice were measured to evaluate the effect of pregnancy on ETV hepatic distribution.

KEY RESULTS

ETV was shown to be a substrate of ENT1 and OAT2. An ENT1 inhibitor significantly decreased the efficacy of ETV in HepG2.2.15 cells, while overexpression of OAT2 increased susceptibility of HBV to ETV. The liver-to-plasma ETV concentration ratios in pregnant mice were sharply reduced; whereas, the absolute concentration of ETV in the liver did not obviously alter in pregnancy. Although oestradiol and progesterone showed a concentration-dependent inhibition on ETV accumulation both in hepatic cell lines and in primary human hepatocytes, a physiologically relevant concentration of oestradiol and progesterone did not affect antiviral activity of ETV.

CONCLUSIONS AND IMPLICATIONS

OAT2 and ENT1 are the main transporters involved in the hepatic uptake and anti-HBV efficacy of ETV. The concentration of ETV in the liver was not obviously altered during pregnancy, which indicates that dosage adjustment in pregnancy is not necessary.

Diagnostic and prognostic value of WNT family gene expression in hepatitis B virus‑related hepatocellular carcinoma

The aim of the present study was to investigate the diagnostic and prognostic value of Wingless-type MMTV integration site (WNT) gene family expression in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). The clinical data of the patients and gene expression levels were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Receiver operating characteristic curve analysis was used to investigate the diagnostic value of WNT genes. Cox proportional hazard regression analysis and Kaplan-Meier survival analysis were performed to evaluate the association of WNT gene expression level with overall survival (OS) and recurrence-free survival (RFS). A nomogram was constructed for the prediction of prognosis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Diagnostic receiver operating characteristic curve analysis suggested that WNT2 had a high diagnostic value, with an area under the curve (AUC) of >0.800 (P<0.0001, AUC=0.810, 95% CI: 0.767–0.852). Survival analysis indicated that the expression level of WNT1 was significantly associated with OS and RFS (adjusted P=0.033, adjusted HR=0.607, 95% CI: 0.384–0.960; and adjusted P=0.007, adjusted HR=0.592, 95% CI: 0.404–0.868, respectively). In the TCGA validation cohort, we also observed that WNT2 was significantly differentially expressed between HCC tissues and adjacent non-tumor tissues, and WNT1 was associated with both the OS and RFS of HCC. Therefore, through the GSE14520 HBV-related HCC cohort we concluded that WNT2 may serve as a diagnostic biomarker and WNT1 may serve as a prognostic biomarker. These results may also be extended to TCGA HCC verification cohort.

A comprehensive study of epigenetic alterations in hepatocellular carcinoma identifies potential therapeutic targets

BACKGROUND & AIMS

A causal link has recently been established between epigenetic alterations and hepatocarcinogenesis, indicating that epigenetic inhibition may have therapeutic potential. We aimed to identify and target epigenetic modifiers that show molecular alterations in hepatocellular carcinoma (HCC).

METHODS

We studied the molecular-clinical correlations of epigenetic modifiers including bromodomains, histone acetyltransferases, lysine methyltransferases and lysine demethylases in HCC using The Cancer Genome Atlas (TCGA) data of 365 patients with HCC. The therapeutic potential of epigenetic inhibitors was evaluated in vitro and in vivo. RNA sequencing analysis and its correlation with expression and clinical data in the TCGA dataset were used to identify expression programs normalized by Jumonji lysine demethylase (JmjC) inhibitors.

RESULTS

Genetic alterations, aberrant expression, and correlation between tumor expression and poor patient prognosis of epigenetic enzymes are common events in HCC. Epigenetic inhibitors that target bromodomain (JQ-1), lysine methyltransferases (BIX-1294 and LLY-507) and JmjC lysine demethylases (JIB-04, GSK-J4 and SD-70) reduce HCC aggressiveness. The pan-JmjC inhibitor JIB-04 had a potent antitumor effect in tumor bearing mice. HCC cells treated with JmjC inhibitors showed overlapping changes in expression programs related with inhibition of cell proliferation and induction of cell death. JmjC inhibition reverses an aggressive HCC gene expression program that is also altered in patients with HCC. Several genes downregulated by JmjC inhibitors are highly expressed in tumor vs. non-tumor parenchyma, and their high expression correlates with a poor prognosis. We identified and validated a 4-gene expression prognostic signature consisting of CENPA, KIF20A, PLK1, and NCAPG.

CONCLUSIONS

The epigenetic alterations identified in HCC can be used to predict prognosis and to define a subgroup of high-risk patients that would potentially benefit from JmjC inhibitor therapy.

LAY SUMMARY

In this study, we found that mutations and changes in expression of epigenetic modifiers are common events in human hepatocellular carcinoma, leading to an aggressive gene expression program and poor clinical prognosis. The transcriptional program can be reversed by pharmacological inhibition of Jumonji enzymes. This inhibition blocks hepatocellular carcinoma progression, providing a novel potential therapeutic strategy.

Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients

BACKGROUND

Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients' prognosis. We aim to identify new prognostic markers for resected HCC patients.

METHODS

274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a "9-gene signature" associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80).

RESULTS

We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001).

CONCLUSIONS

The 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions.

Diagnostic and prognostic significance of mRNA expressions of apolipoprotein A and C family genes in hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is among the most common and lethal malignancies worldwide. Apolipoproteins (APOs) have been reported increasingly for their relationships with tumors. We aim at exploring the potential relationships of apolipoprotein A (APOA) and apolipoprotein C (APOC) family members with HCC.

METHODS

A data set, containing 212 hepatitis B virus-related HCC patients, was used for analysis. The diagnostic and prognostic ability of APOA and APOC family genes was figured out. Risk score models and nomograms were developed for the HCC prognosis prediction. Moreover, molecular mechanism exploration were identified biological processes and metabolic pathways of these genes involved in. Validation analysis was carried out using online website.

RESULTS

APOA1, APOC1, APOC3, and APOC4 showed robust diagnosis significance (all P < 0.05). APOA4, APOC3, and APOC4 were associated with the overall survival (OS) while APOA4 and APOC4 were linked to recurrence-free survival (RFS, all P ≤ 0.05). Risk score models and nomograms had the advantage of predicting OS and RFS for HCC. Molecular mechanism exploration indicated that these genes were involved in the steroid metabolic process, the PPAR signaling pathway, and fatty acid metabolism. Besides that, validation analysis revealed that APOC1 and APOC4 had an association with OS; and APOC3 was associated with OS and RFS (all P ≤ 0.05).

CONCLUSIONS

APOA1, APOC1, APOC3, and APOC4 are likely to be potential diagnostic biomarkers and APOC3 and APOC4 are likely to be potential prognostic biomarkers for hepatitis B virus-related HCC. They may be involved in the steroid metabolic process, PPAR signaling pathway, and fatty acid metabolism.

Clustered microRNAs hsa-miR-221-3p/hsa-miR-222-3p and their targeted genes might be prognostic predictors for hepatocellular carcinoma

Objective: MicroRNAs (miRNAs) have been explored in malignancies. We investigated the functions of clustered miRNAs hsa-miR-221/222-3p in hepatocellular carcinoma (HCC). Methods: Human miRNA tissue atlas website was determined expression levels in liver tissue. Four databases, TarBase, miRTarBase, miRecords and miRPathDB, were found experimentally validated target genes of clustered miRNAs. TargetScanHuman was predicted target genes. The STRING website was depicted protein-protein interaction (PPI) networks. The OncoLnc website analyzed prognostic values for hsa-miR-221/222-3p and their target genes. The MCODE plugin calculated modules of PPI networks. Receiver operating characteristic (ROC) curves were predicted 1, 3, and 5 years prognostic values. Results: Expression of clustered miRNAs was high in liver tissues. A total of 1577 target genes were identified. Enrichment analysis showed that target genes were enriched mainly in cancer, Wnt signaling and ErbB signaling pathways. Two modules were calculated using PPI networks. Has-miR-221-3p was not associated with prognosis (P = 0.401). Has-miR-222-3p and target genes ESR1, TMED7, CBFB, ETS2, UBE2J1 and UBE2N of the clustered miRNAs were associated with HCC survival (all P < 0.05). Has-miR-222-3p, CBFB, and UBE2N showed good performance of ROC in prognosis prediction at 1, 3, and 5 years (all area under curves > 0.600). Conclusion: Has-miR-222-3p and target genes, especially CBFB, UBE2N, may serve as prognostic predictors for HCC.

Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases

Hepatocellular carcinoma (HCC) ranks the third major cause of cancer-associated mortality globally. Numerous studies have attempted to elucidate the underlying mechanisms of HCC using various biomarkers. In the present study, two expression profiles datasets from Gene Expression Omnibus (GSE76427 and GSE84402) and data associated with liver cancer samples from The Cancer Genome Atlas (TCGA) were downloaded for integrated analysis. Five differentially expressed genes (DEGs) exhibiting high expression, including ubiquitin-conjugating enzyme 2C (UBE2C), topoisomerase II α, pituitary tumor transforming gene 1, glypican-3 and polycomb-repressive complex 1, were selected and considered as candidate genes. Enrichment analysis demonstrated that these genes were associated with Gene Ontology terms of cellular components and molecular functions, including regulation of apoptosis, stabilization of p53 and Anaphase Promoting Complex/Cyclosome (APC/C) (APC/C:Cdc20)-mediated degradation of Securin. The expression profiles of these genes in HCC, other human malignancies and different human HCC cell lines were validated using GSE14520, GSE3500 and TCGA data. The results confirmed the upregulation of UBE2C in tissues from patients with HCC or other human malignancies and human liver cancer cell lines, compared with the expression levels in the corresponding adjacent non-tumor tissues and cell lines, respectively. Patients with HCC who exhibited an increased messenger RNA level of UBE2C exhibited a significantly shorter survival time. The results of the present study suggest that the overexpression of UBE2C may be used as a novel prognostic biomarker of HCC.

Pathway-based biomarker identification with crosstalk analysis for robust prognosis prediction in hepatocellular carcinoma

BACKGROUND

Although many prognostic single-gene (SG) lists have been identified in cancer research, application of these features is hampered due to poor robustness and performance on independent datasets. Pathway-based approaches have thus emerged which embed biological knowledge to yield reproducible features.

METHODS

Pathifier estimates pathways deregulation score (PDS) to represent the extent of pathway deregulation based on expression data, and most of its applications treat pathways as independent without addressing the effect of gene overlap between pathway pairs which we refer to as crosstalk. Here, we propose a novel procedure based on Pathifier methodology, which for the first time has been utilized with crosstalk accommodated to identify disease-specific features to predict prognosis in patients with hepatocellular carcinoma (HCC).

FINDINGS

With the cohort (N = 355) of HCC patients from The Cancer Genome Atlas (TCGA), cross validation (CV) revealed that PDSs identified were more robust and accurate than the SG features by deep learning (DL)-based approach. When validated on external HCC datasets, these features outperformed the SGs consistently.

INTERPRETATION

On average, we provide 10.2% improvement of prediction accuracy. Importantly, governing genes in these features provide valuable insight into the cancer hallmarks of HCC. We develop an R package PATHcrosstalk (available from GitHub https://github.com/fabotao/PATHcrosstalk) with which users can discover pathways of interest with crosstalk effect considered.

Genetic Polymorphisms Predisposing the Interleukin 6-Induced APOBEC3B-UNG Imbalance Increase HCC Risk via Promoting the Generation of APOBEC-Signature HBV Mutations

PURPOSE

APOBEC3-UNG imbalance contributes to hepatitis B virus (HBV) inhibition and somatic mutations. We aimed to explore the associations between hepatocellular carcinoma (HCC) risk and genetic polymorphisms predisposing the imbalance.Experimental Design: Genetic polymorphisms at APOBEC3 promoter and UNG enhancer regions were genotyped in 5,621 participants using quantitative PCR. HBV mutations (nt.1600-nt.1945, nt.2848-nt.155) were determined by Sanger sequencing. Dual-luciferase reporter assay was applied to detect the transcriptional activity. Effects of APOBEC3B/UNG SNPs and expression levels on HCC prognosis were evaluated with a cohort of 400 patients with HCC and public databases, respectively.

RESULTS

APOBEC3B rs2267401-G allele and UNG rs3890995-C allele significantly increased HCC risk. rs2267401-G allele was significantly associated with the generation of APOBEC-signature HBV mutation whose frequency consecutively increased from asymptomatic HBV carriers to patients with HCC. Multiplicative interaction of rs2267401-G allele with rs3890995-C allele increased HCC risk, with an adjusted OR (95% confidence interval) of 1.90 (1.34-2.81). rs2267401 T-to-G and rs3890995 T-to-C conferred increased activities of APOBEC3B promoter and UNG enhancer, respectively. IL6 significantly increased APOBEC3B promoter activity and inhibited UNG enhancer activity, and these effects were more evident in those carrying rs2267401-G and rs3890995-C, respectively. APOBEC3B rs2267401-GG genotype, higher APOBEC3B expression, and higher APOBEC3B/UNG expression ratio in HCCs indicated poor prognosis. APOBEC-signature somatic mutation predicts poor prognosis in HBV-free HCCs rather than in HBV-positive ones.

CONCLUSIONS

Polymorphic genotypes predisposing the APOBEC3B-UNG imbalance in IL6-presenting microenvironment promote HCC development, possibly via promoting the generation of high-risk HBV mutations. This can be transformed into specific prophylaxis of HBV-caused HCC.

Prognostic Value of Gamma-Glutamyl Transpeptidase to Lymphocyte Count Ratio in Patients With Single Tumor Size ≤ 5 cm Hepatocellular Carcinoma After Radical Resection

Prediction of prognosis of hepatocellular carcinoma (HCC) has shown an important role in improving treatment outcomes and preventing disease progression, however, the prognostic indicator of HCC is still lacking. The purpose of this study is to investigate the predictive value of GLR (gamma-glutamyl transpeptidase to lymphocyte count ratio) in single HCC with a tumor size (TS) ≤ 5 cm. A retrospective analysis was performed on 272 patients with TS ≤ 5 cm who underwent radical resection. The Pearson χ² test was applied to discuss the relationship between HCC and GLR, alpha-fetoprotein (AFP). Then univariate and multivariate analysis was utilized to predict the risk factors for survival prognosis in patients. In this study, GLR showed a positive relation with tumor size, tumor-node-metastasis (TNM) stage, microvascular invasion, early recurrence, and serum aspartate aminotransferase (AST) level, while the AFP value only correlated with drinking. Elevated GLR value had poor overall survival (OS) and progression-free survival (PFS) of TS ≤ 5 cm HCC patients, GLR level and tumor size were closely related to the prognosis of small HCC patients compared with AFP. GLR may serve as a prognostic marker for dynamic monitoring of HCC patients with single TS ≤ 5 cm after radical resection.

Identification of a six-gene signature predicting overall survival for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) remains a major challenge for public health worldwide. Considering the great heterogeneity of HCC, more accurate prognostic models are urgently needed. To identify a robust prognostic gene signature, we conduct this study.

Materials and methods

Level 3 mRNA expression profiles and clinicopathological data were obtained in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). GSE14520 dataset from the gene expression omnibus (GEO) database was downloaded to further validate the results in TCGA. Differentially expressed mRNAs between HCC and normal tissue were investigated. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC), Kaplan–Meier curve, multivariate Cox regression analysis, nomogram, and decision curve analysis (DCA) were used to assess the prognostic capacity of the six-gene signature. The prognostic value of the gene signature was further validated in independent GSE14520 cohort. Gene Set Enrichment Analyses (GSEA) was performed to further understand the underlying molecular mechanisms. The performance of the prognostic signature in differentiating between normal liver tissues and HCC were also investigated.

Results

A novel six-gene signature (including CSE1L, CSTB, MTHFR, DAGLA, MMP10, and GYS2) was established for HCC prognosis prediction. The ROC curve showed good performance in survival prediction in both the TCGA HCC cohort and the GSE14520 validation cohort. The six-gene signature could stratify patients into a high- and low-risk group which had significantly different survival. Cox regression analysis showed that the six-gene signature could independently predict OS. Nomogram including the six-gene signature was established and shown some clinical net benefit. Furthermore, GSEA revealed several significantly enriched oncological signatures and various metabolic process, which might help explain the underlying molecular mechanisms. Besides, the prognostic signature showed a strong ability for differentiating HCC from normal tissues.

Conclusions

Our study established a novel six-gene signature and nomogram to predict overall survival of HCC, which may help in clinical decision making for individual treatment.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0858-2) contains supplementary material, which is available to authorized users.