Potential Biomarker For Hepatocellular Carcinoma Research Articles

Increased expression of long non-coding RNA FIRRE promotes hepatocellular carcinoma by HuR-CyclinD1 axis signaling

There is a critical need to understand the disease processes and identify improved therapeutic strategies for hepatocellular carcinoma (HCC). The long noncoding RNAs (lncRNAs) display diverse effects on biological regulations. The aim of this study was to identify a lncRNA as a potential biomarker of HCC and investigate the mechanisms by which the lncRNA promotes HCC progression using human cell lines and in vivo. Using RNA-Seq analysis, we found that lncRNA FIRRE was significantly upregulated in hepatitis C virus (HCV) associated liver tissue and identified that lncRNA FIRRE is significantly upregulated in HCV associated HCC compared to adjacent non-tumor liver tissue. Further, we observed that FIRRE is significantly upregulated in HCC specimens with other etiologies, suggesting this lncRNA has a potential to serve as an additional biomarker for HCC. Overexpression of FIRRE in hepatocytes induced cell proliferation, colony formation, and xenograft tumor formation as compared to vector transfected control cells. Using RNA pull-down proteomics, we identified HuR as an interacting partner of FIRRE. We further showed that the FIRRE-HuR axis regulates cyclin D1 expression. Our mechanistic investigation uncovered that FIRRE is associated with an RNA binding protein HuR for enhancing hepatocyte growth. Together, these findings provide molecular insights into the role of FIRRE in HCC progression.

Network-base approaches to identify therapeutic biomarkers in hepatocellular carcinoma and search for drug hunting utilizing molecular dynamics simulations

The presence of conditions like Alpha-1 antitrypsin deficiency, hemochromatosis, non-alcoholic fatty liver diseases and metabolic syndrome can elevate the susceptibility to hepatic cellular carcinoma (HCC). Utilizing network-based gene expression profiling via network analyst tools, presents a novel approach for drug target discovery. The significance level (p-score) obtained through Cytoscape in the intended center gene survival assessment confirms the identification of all target center genes, which play a fundamental role in disease formation and progression in HCC. A total of 1064 deferential expression genes were found. These include MCM2 with the highest degree, followed by 4917 MCM6 and MCM4 with a 3944-degree score. We investigated the regulatory kinases involved in establishing the protein-protein interactions network using X2K web tool. The docking approach yields a favorable binding affinity of −8.7 kcal/mol against the target MCM2 using Auto-Dock Vina. Interestingly after simulating the complex system via AMBER16 package, results showed that the root mean square deviation values remained within 4.74 Å for a protein and remains stable throughout the time intervals. Additionally, the ligand’s fit to the protein exhibited fluctuations at some intervals but remains stable. Finally, Gibbs free energy was found to be at its lowest at 1 kcal/mol which presents the real time interactive binding of the atomic residues among inhibitor and protein. The displacement of the ligand was measured showing stable movement and displacement along the active site. These findings increased our understanding for potential biomarkers in hepatocellular carcinoma and an experimental approach will further enhance our outcomes in future. Communicated by Ramaswamy H. Sarma

Combinatorial Gene Expression Profiling of Serum HULC, HOTAIR, and UCA1 lncRNAs to Differentiate Hepatocellular Carcinoma from Liver Diseases: A Systematic Review and Meta-Analysis.

Hepatocellular carcinoma (HCC) presents a significant global health challenge due to limited early detection methods, primarily relying on conventional approaches like imaging and alpha-fetoprotein (AFP). Although non-coding RNAs (ncRNAs) show promise as potential biomarkers in HCC, their true utility remains uncertain. We conducted a comprehensive review of 76 articles, analyzing 88 circulating lncRNAs in 6426 HCC patients. However, the lack of a standardized workflow protocol has hampered holistic comparisons across the literature. Consequently, we herein confined our meta-analysis to only a subset of these lncRNAs. The combined analysis of serum highly upregulated in liver cancer (HULC) gene expression with homeobox transcript antisense intergenic RNA (HOTAIR) and urothelial carcinoma-associated 1 (UCA1) demonstrated markedly enhanced sensitivity and specificity in diagnostic capability compared to traditional biomarkers or other ncRNAs. These findings could have substantial implications for the early diagnosis and tailored treatment of HCC.

Constructed Risk Prognosis Model Associated with Disulfidptosis lncRNAs in HCC.

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan-Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

STC2 is a potential biomarker of hepatocellular carcinoma with its expression being upregulated in Nrf1α-deficient cells, but downregulated in Nrf2-deficient cells

Nrf1 (encoded by Nfe2l1) and Nrf2 (encoded by Nfe2l2), as two key members of the CNC-bZIP transcription factor, exhibit significant functional differences in their pathophysiology. Our previous findings demonstrated that loss of Nrf1α (i.e., a full-length isoform of Nrf1) promotes HepG2-derived tumor growth in xenograft mice, but malgrowth of the xenograft tumor is significantly suppressed by knockout of Nrf2. To gain insights into the mechanism underlying such marked distinctions in their pathologic phenotypes, we mined transcriptome data from liver cancer in the TCGA database to establish a prognostic model and calculate predicted risk scores for each cell line. The results revealed that knockout of Nrf1α markedly increased the risk score in HepG2 cells, whereas the risk score was reduced by knockout of Nrf2. Notably, stanniocalcin 2 (STC2), a biomarker associated with liver cancer, that is upexpressed in hepatocellular carcinoma (HCC) tissues with a reduction in the overall survival ratio of those patients. We observed increased expression levels of STC2 in Nrf1α−/− cells but decreased expression in Nrf2−/− cells. These findings suggested that STC2 may play a role in mediating the distinction between Nrf1α−/− and Nrf2−/−. Such potential function of STC2 was further corroborated through a series of experiments combined with transcriptomic sequencing. The results revealed that STC2 functions as a dominant tumor-promoter, because the STC2-leading increases in clonogenicity of hepatoma cells and malgrowth of relevant xenograft tumor were almost completely abolished in STC2−/− cells. Together, these demonstrate that STC2 could be paved as a potential therapeutic target, albeit as a diagnostic marker, for HCC.

Cellular senescence-related genes: predicting prognosis in hepatocellular carcinoma

Recent studies have shown that the high incidence and low cure rate of hepatocellular carcinoma (HCC) have not improved significantly. Surgery and liver transplantation are the mainstays of prolonging the survival of HCC patients. However, the surgical resection rate of HCC patients is very low, and even after radical surgical resection, the recurrence rate at 5 years postoperatively remains high and the prognosis is very poor, so more treatment options are urgently needed. Increasing evidence suggests that cellular senescence is not only related to cancer development but may also be one of its primary driving factors. We aimed to establish a prognostic signature of senescence-associated genes to predict the prognosis and therapeutic response of HCC patients. The aim of this study was to develop a risk model associated with cellular senescence and to search for potential strategies to treat HCC. We divided HCC patients into two clusters and identified differentially expressed genes (DEGs) between clusters. In this study, low-risk patients had a better prognosis, higher levels of immune cell infiltration, and better efficacy to fluorouracil, Paclitaxel and Cytarabine chemotherapy compared to high-risk patients. To further identify potential biomarkers for HCC, we further validated the expression levels of the four signature genes in HCC and neighbouring normal tissues by in vitro experiments. In conclusion, we identified and constructed a relevant prognostic signature, which performed well in predicting the survival and treatment response of HCC patients. This helps to differentiate between low-score and high-risk HCC, and the results may contribute to precise treatment protocols in clinical practice.

Protein profiles reveal MSH6/MSH2 as a potential biomarker for hepatocellular carcinoma with microvascular invasion.

Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence and metastasis in hepatocellular carcinoma (HCC). However, the specific protein expression profiles that differentiate HCC with MVI from those without MVI remain unclear. The profiles of proteins in early-stage HCC tissues and normal liver tissues were characterized by quantitative proteomics techniques. Immunohistochemical (IHC) staining was undertaken on tissue microarrays from 80 HCC patients to assess the expression of MSH2 and MSH6. Cell counting, colony formation, migration, and invasion assays were carried out in vitro. We identified 5164 proteins in both HCC tissues and adjacent normal liver tissues. Compared to HCC without MVI, 148 upregulated proteins and 97 downregulated proteins were found in HCC with MVI. Particularly noteworthy was the remarkable upregulation of MSH6/MSH2 among these dysregulated proteins in HCC with MVI. Further validation through bioinformatics prediction and IHC confirmed the elevated expression of MSH6/MSH2, which correlated with aggressive disease characteristics and poor prognosis. Receiver operating characteristic curve analyses revealed a substantial area under the curve of 0.761 (specificity 71.79%, sensitivity 73.17%) for the combined use of MSH6/MSH2. Knockdown of MSH6/MSH2 significantly inhibited HCC cell proliferation and invasion in vitro. Our study establishes MSH6 or MSH2 as an oncogene that is prominently overexpressed during HCC progression, which provides new targets for HCC with MVI.

Glutamine metabolic reprogramming in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a lethal disease with limited management strategies and poor prognosis. Metabolism alternations have been frequently unveiled in HCC, including glutamine metabolic reprogramming. The components of glutamine metabolism, such as glutamine synthetase, glutamate dehydrogenase, glutaminase, metabolites, and metabolite transporters, are validated to be potential biomarkers of HCC. Increased glutamine consumption is confirmed in HCC, which fuels proliferation by elevated glutamate dehydrogenase or upstream signals. Glutamine metabolism also serves as a nitrogen source for amino acid or nucleotide anabolism. In addition, more glutamine converts to glutathione as an antioxidant in HCC to protect HCC cells from oxidative stress. Moreover, glutamine metabolic reprogramming activates the mTORC signaling pathway to support tumor cell proliferation. Glutamine metabolism targeting therapy includes glutamine deprivation, related enzyme inhibitors, and transporters inhibitors. Together, glutamine metabolic reprogramming plays a pivotal role in HCC identification, proliferation, and progression.

CircCPSF6 promotes hepatocellular carcinoma cancer progression by regulating MAP4K4 through sponging miR-145-5p

BackgroundAberrant expression of circRNAs is involved in the progression of hepatocellular carcinoma (HCC). This study aimed at screening the pro-tumorigenic circular RNAs (circRNAs) in HCC and the mechanisms of circCPSF6 expression influencing HCC characteristics. MethodcircCPSF6 was identified in HCC tissues using high-throughput sequencing data, and its expression was verified in both HCC tissues and cell lines using quantitative real-time PCR (qRT-PCR). CCK-8 and Transwell assays were used to evaluate the effects of circCPSF6 on HCC proliferation and migration. A xenograft mouse model was used to investigate the effects of circCPSF6 on HCC progression in vivo, and the significance of circCPSF6 in HCC was verified both in vivo and in vitro. circCPSF6-associated miRNAs and mRNAs were identified using bioinformatic analyses. Luciferase reporter, RNA pull-down, Fluorescence in situ hybridization, and RNA immunoprecipitation assays were performed to elucidate the circCPSF6 regulatory axis in HCC. ResultCircCPSF6 expression was increased in HCC cell lines and tissues, and the expression of its parental mRNA was positively correlated with tumor severity and negatively correlated with survival. Mechanistic analyses of HCC cell lines showed that tumorigenesis was inhibited by circCPSF6 knockdown and promoted by its overexpression. Functional analyses revealed that circCPSF6 mediated HCC development by sponging miR-145-5p as a competing endogenous RNA. Furthermore, this sponging upregulated the miR-145-5p target gene MAP4K4, a classical pro-tumorigenic gene. ConclusionOur findings reveal a regulatory network that includes the circCPSF6–miR-145-5p–MAP4K4 axis. Elements of this axis are potential HCC biomarkers, as well as targets for HCC treatment.

Risk prediction for dermatomyositis-associated hepatocellular carcinoma

ObjectiveTo explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms.MethodsBased on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated.ResultsThe expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma.ConclusionLY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma.

Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major health problem around the world. The management of this disease is complicated by the lack of noninvasive diagnostic tools and the few treatment options available. Better clinical outcomes can be achieved if HCC is detected early, but unfortunately, clinical signs appear when the disease is in its late stages. We aim to identify novel genes that can be targeted for the diagnosis and therapy of HCC. We performed a meta-analysis of transcriptomics data to identify differentially expressed genes and applied network analysis to identify hub genes. Fatty acid metabolism, complement and coagulation cascade, chemical carcinogenesis and retinol metabolism were identified as key pathways in HCC. Furthermore, we integrated transcriptomics data into a reference human genome-scale metabolic model to identify key reactions and subsystems relevant in HCC. We conclude that fatty acid activation, purine metabolism, vitamin D, and E metabolism are key processes in the development of HCC and therefore need to be further explored for the development of new therapies. We provide the first evidence that GABRP, HBG1 and DAK (TKFC) genes are important in HCC in humans and warrant further studies.

Over-expression of RRM2 predicts adverse prognosis correlated with immune infiltrates: A potential biomarker for hepatocellular carcinoma.

Ribonucleotide reductase regulatory subunit M2 (RRM2) has been reported to be an oncogene in some malignant tumors, such as lung adenocarcinoma, oral squamous cell carcinoma, glioblastoma, and breast cancer. However, the clinical significance of RRM2 in hepatocellular carcinoma has been less studied. The aim of this study was to assess the importance of RRM2 in hepatocellular carcinoma (HCC) based on the Cancer Genome Atlas (TCGA) database. The RRM2 expression levels and clinical features were downloaded from the TCGA database. Immunohistochemistry results between tumor tissues and normal tissues were downloaded from the Proteinatlas database. Meanwhile, the expression levels of RRM2 in tumor and paraneoplastic tissues were further verified by qRT-PCR and Western Blotting. Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein-interactions (PPI) network were constructed to analyze RRM2-related downstream molecules. In addition, RRM2 expression-related pathways performed by gene set enrichment analysis (GSEA). Association analysis of RRM2 gene expression and immune infiltration was performed by single-sample GSEA (ssGSEA). The RRM2 expression level in tumor tissues was higher than normal tissues (P <0.001). The elevated expression of RRM2 in HCC was significantly correlated with T stage (P <0.05), pathologic stage (P <0.05), tumor status (P <0.05), histologic grade (P<0.001), and AFP (P <0.001). HCC with higher RRM2 expression was positively associated with worse OS (overall survival), PFS (progression-free survival), and DSS (disease-specific survival). In the univariate analysis, the expression of RRM2, T stage, M stage, pathologic stage, and tumor status were negatively correlated with OS (P <0.05). Further analysis using multivariate Cox regression showed that tumor status (P<0.01) and RRM2 expression (P<0.05) were independent prognostic factors of OS in HCC. GO/KEGG analysis showed that the critical biological process (chromosome condensation and p53 signaling pathway) might be the possible function mechanism in promoting HCC. Moreover, GSEA showed that several pathways were enriched in RRM2 high-expression samples, including PD-1 signaling, cell cycle, P27 pathway, and T cell receptor signaling pathway. RRM2 was significantly correlated with the infiltration level of CD8 T cells, Cytotoxic cells, DCs, Neutrophils, NK cells, and T helper cells (P <0.05). Over-expression of RRM2 predict adverse prognosis and is correlated with immune infiltrates in HCC. RRM2 may be a significant molecular biomarker for HCC diagnosis and prognosis.

Aberrant DNA Methylation Patterns of Deleted in Liver Cancer 1 Isoforms in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), a common primary liver cancer, is the third leading cause of death worldwide. DNA methylation changes are common in HCC and have been studied to be associated with hepatocarcinogenesis. In our study, we used the MassARRAY® EpiTYPER technology to investigate the methylation differences of deleted in liver cancer 1 (DLC1) (isoform 1 and 3) promoter between HCC tissues and corresponding adjacent noncancerous tissues and the association between methylation levels and clinicopathological features. In addition, the modified CRISPR-Cas9 system and the DNA methyltransferase inhibitor (DNMTi) were utilized to explore the functional correlation of epigenetic modifications and DLC1 gene regulation. The methylation levels of the DLC1 isoforms in HCC samples were found significantly lower than those in the adjacent noncancerous tissues (all p < 0.0001). Also, we found that the expression of DLC1 could be bidirectionally regulated by the modified CRISPR-Cas9 system and the DNMTi. Moreover, the hypomethylation of DLC1 in HCC samples was connected with the presence of satellite lesions (p = 0.0305) and incomplete tumor capsule (p = 0.0204). Receiver operator characteristic curve analysis demonstrated that the methylation levels of DLC1 could be applied to discriminate HCC patients (area under the curve = 0.728, p < 0.0001). The hypomethylation status was a key regulatory mechanism of DLC1 expression and might serve as a potential biomarker for HCC.

Neuropilins as potential biomarkers in hepatocellular carcinoma: a systematic review of basic and clinical implications.

Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers worldwide and is characterized by complex molecular carcinogenesis. Neuropilins (NRPs) NRP1 and NRP2 are the receptors of multiple proteins involved in key signaling pathways associated with tumor progression. We aimed to systematically review all the available findings on their role in HCC. We searched the Scopus, Web of Science (WOS), PubMed, Cochrane and Embase databases for articles evaluating NRPs in preclinical or clinical HCC models. This study was registered in PROSPERO (CRD42022349774) and include 49 studies. Multiple cellular and molecular processes have been associated with one or both NRPs, indicating that they are potential diagnostic and prognostic biomarkers in HCC patients. Mainly NRP1 has been shown to promote tumor cell survival and progression by modulating several signaling pathways. NRPs mainly regulate angiogenesis, invasion and migration and have shown to induce invasion and metastasis. They also regulate the immune response and tumor microenvironment, showing a crucial interplay with the hypoxia response and microRNAs in HCC. Altogether, NRP1 and NRP2 are potential biomarkers and therapeutic targets, providing novel insight into the clinical landscape of HCC patients.

A Space-Dependent 'Enzyme-Substrate' Type Probe based on 'Carboxylesterase-Amide Group' for Ultrafast Fluorescent Imaging Orthotopic Hepatocellular Carcinoma.

Fast and selective fluorescence imaging for a biomarker to related-disease diagnosis remains a significant challenge due to complex physical environment. Human carboxylesterase (CE) is expected to be a potential biomarker of hepatocellular carcinoma (HCC) to improve the accuracy of diagnosis. However, existing probes for CE has slow response rate and low selectivity. Herein, the amide group is selected as CE-responsive sites based on the "substrate-hydrolysis enzymatic reaction" approach. From a series of off-on probes with leave groups in the amide unit, probe JFast is screened with the optimal combination of rapid response rate and high selectivity toward CE. JFast requires only 150s to reach the maximum fluorescence at 676nm in the presence of CE and free from the interference of other esterase. Computational docking simulations indicate the shortest distance between the CE and active site of JFast . Cell and in vivo imaging present that the probe can turn on the liver cancer cells and tumor region precisely. Importantly, JFast is allowed to specifically image orthotopic liver tumor rather than metastatic tumor and distinguish human primary liver cancer tissue from adjacent ones. This study provides a new tool for CE detection and promotes advancements in accurate HCC diagnosis.

The role of serum visfatin and vaspin in hepatocellular carcinoma in hepatitis C-related liver cirrhosis.

To investigate the role of the novel adipokines visfatin and vaspin in hepatitis C virus (HCV)-cirrhotic patients with and without hepatocellular carcinoma (HCC) and their association with tumour characteristics and liver dysfunction. This case-control study was carried out between March 2021 and September 2021. Serum visfatin and vaspin were measured in 67 HCV-cirrhotic patients (37 had HCC, and 30 did not) and 20 healthy individuals using enzyme-linked immunosorbent assay (ELISA). Serum visfatin and vaspin were substantially elevated in HCC patients compared to those without HCC and healthy controls (p = 0.001, < 0.0001, respectively) and significantly associated with hepatic dysfunction. At a cut-off value of 12.1 ng/ml, the sensitivity and specificity of the serum visfatin in detecting HCC were 67.6% and 83.3%, respectively. Serum vaspin at a cut-off value of 321 ng/dl had a sensitivity of 94.6% and specificity of 66.7%. In multivariate regression analysis, serum vaspin and albumin were independent risk factors for HCC development. Patients with Barcelona Clinic Liver Cancer (BCLC) stage D had significantly the highest serum levels of visfatin and vaspin (p = 0.03, 0.008, respectively). Serum visfatin and vaspin were substantially higher in HCC patients, associated with tumour stage, and might be considered as potential biomarkers of HCC, but this should be confirmed in larger independent cohorts of patients with liver cirrhosis. Serum vaspin and albumin were independent risk factors for HCC development. There was a substantial association between visfatin, vaspin, and the severity of the underlying liver dysfunction.

Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma.

Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes. We screened differentially expressed proteins between tumorous and adjacent nontumorous tissues of hepatitis B virus (HBV)-related HCC patients using a Nanoscale Liquid Chromatography-Tandem Mass Spectrometry platform and combined it with transcriptomic data of lipid-metabolism-related genes from the GEO and HPA databases to identify dysregulated genes that may be involved in lipid metabolic processes. The potential clinical values of these genes were explored by bioinformatics online analysis tools (GEPIA, cBioPortal, SurvivalMeth, and TIMER). The expression levels of the secreted protein (angiopoietin-like protein 6, ANGPTL6) in serum were analyzed by ELISA. The ability of serum ANGPTL6 to diagnose early HCC was assessed by ROC curves. The results showed that serum ANGPTL6 could effectively differentiate between HBV-related early HCC patients with normal serum alpha-fetoprotein (AFP) levels and the noncancer group (healthy participants and chronic hepatitis B patients) (AUC = 0.717, 95% CI: from 0.614 to 0.805). Serum ANGPTL6 can be used as a potential second-line biomarker to supplement serum AFP in the early diagnosis of HBV-related HCC.

Identification of Hypoxia-Related Prognostic Signature and Competing Endogenous RNA Regulatory Axes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common type of liver cancer and one of the highly lethal diseases worldwide. Hypoxia plays an important role in the development and prognosis of HCC. This study aimed to construct a new hypoxia-related prognosis signature and investigate its potential ceRNA axes in HCC. RNA profiles and hypoxia genes were downloaded, respectively, from the Cancer Genome Atlas hepatocellular carcinoma database and Gene Set Enrichment Analysis website. Cox regression analyses were performed to select the prognostic genes and construct the risk model. The ENCORI database was applied to build the lncRNA-miRNA-mRNA prognosis-related network. The TIMER and CellMiner databases were employed to analyze the association of gene expression in ceRNA with immune infiltration and drug sensitivity, respectively. Finally, the co-expression analysis was carried out to construct the potential lncRNA/miRNA/mRNA regulatory axes. We obtained a prognostic signature including eight hypoxia genes (ENO2, KDELR3, PFKP, SLC2A1, PGF, PPFIA4, SAP30, and TKTL1) and further established a hypoxia-related prognostic ceRNA network including 17 lncRNAs, six miRNAs, and seven mRNAs for hepatocellular carcinoma. Then, the analysis of immune infiltration and drug sensitivity showed that gene expression in the ceRNA network was significantly correlated with the infiltration abundance of multiple immune cells, the expression level of immune checkpoints, and drug sensitivity. Finally, we identified three ceRNA regulatory axes (SNHG1/miR-101-3p/PPFIA4, SNHG1/miR-101-3p/SAP30, and SNHG1/miR-101-3p/TKTL1) associated with the progression of HCC under hypoxia. Here, we constructed a prognosis gene signature and a ceRNA network related to hypoxia for hepatocellular carcinoma. Among the ceRNA network, six highly expressed lncRNAs (AC005540.1, AC012146.1, AC073529.1, AC090772.3, AC138150.2, AL390728.6) and one highly expressed mRNA (PPFIA4) were the potential biomarkers of hepatocellular carcinoma which we firstly reported. The three predicted hypoxia-related regulatory axes may play a vital role in the progression of hepatocellular carcinoma.

Comprehensive Analysis of the Expression and Prognosis for Lipid Metabolism-Related Genes in Hepatocellular Carcinoma.

Hao DingBackground This study aimed to screen potential key genes associated with lipid metabolism and to evaluate their expressions and prognosis values in hepatocellular carcinoma (HCC). Methods Data sets GSE6764, GSE14520, and GSE112790 were used to identify the common differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed by STRING database. Hub genes in PPI network were identified and subjected to functional enrichment analysis to screen lipid metabolism-related genes. The expressions of selected genes and their associations with prognosis were analyzed using UALCAN, The Human Protein Atlas, and Kaplan-Meier plotter databases. The transcriptional factor (TF)-gene regulatory network was constructed using NetworkAnalyst. Results A total of 331 common DEGs including 106 upregulated and 225 downregulated genes were identified. PPI network analysis showed that 76 genes with high degrees were identified as hub genes, among which 14 genes were lipid metabolism-related genes. PON1, CYP2C9, and SPP1 were found to be the independent prognostic markers. Key TFs with close interactions with these prognostic genes, including HINFP, SRF, YY1, and NR3C1, were identified from the TF-gene regulatory network. Conclusion This study presented evidence for the prognostic capabilities of lipid metabolism-related genes in HCC, and newly identified HINFP and NR3C1 as potential biomarkers for HCC.

Comprehensive evaluation of microRNA as a biomarker for the diagnosis of hepatocellular carcinoma.

BACKGROUNDHepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Current guidelines for HCC management recommend surveillance of high-risk patients every 6 mo using ultrasonography. Serum biomarkers, like alpha-fetoprotein (AFP), protein induced by vitamin K absence/antagonist-II (PIVKA-II) and lectin-reactive AFP, show suboptimal performance for detection of HCC, which is crucial for successful resection or treatment. Thus, there is a significant need for new biomarkers to aid early diagnosis of HCC. Studies have shown that the expression level of human microRNAs (miRNAs), a small, non-coding RNA species released into the blood, can serve as an early marker for various diseases, including HCC.AIMTo evaluate the diagnostic role of miRNAs in HCC as single markers, signatures or in combination with known protein biomarkers.METHODSOur prospective, multicenter, case-control study recruited 660 participants (354 controls with chronic liver disease and 306 participants with HCC) and employed a strategy of initial screening by two independent methods, real-time quantitative PCR (n = 60) and next-generation sequencing (n = 100), to assess a large number of miRNAs. The results from the next-generation sequencing and real-time quantitative PCR screening approaches were then combined to select 26 miRNAs (including two putative novel miRNAs). Those miRNAs were analyzed for their diagnostic potential as single markers or in combination with other miRNAs or established protein biomarkers AFP and PIVKA-II via real-time quantitative PCR in training (n = 200) and validation cohorts (n = 300).RESULTSWe identified 26 miRNAs that differentiated chronic liver disease controls from (early) HCC via two independent discovery approaches. Three miRNAs, miR-21-5p (miR-21), miR-320a and miR-186-5p, were selected by both methods. In the training cohort, only miR-21, miR-320d and miR-423 could significantly distinguish (Q < 0.05) between the HCC and chronic liver disease control groups. In the multivariate setting, miR-21 with PIVKA-II was selected as the best combination, resulting in an area under the curve of 0.87 for diagnosis and area under the curve of 0.74 for early diagnosis of HCC. In the validation cohort, only miR-21 and miR-423 could be confirmed as potential HCC biomarkers. A combination of miRNAs did not perform better than any single miRNA. Improvement of PIVKA-II performance through combination with miRNAs could not be confirmed in the validation panel. Two putative miRs, put-miR-6 and put-miR-99, were tested in the training and validation panels, but their expression could only be detected in very few samples and at a low level (cycle threshold between 31.24 and 34.97).CONCLUSIONmiRNAs alone or as a signature in combination with protein biomarkers AFP and PIVKA-II do not improve the diagnostic performance of the protein biomarkers.