OncoDB.HCC: an integrated oncogenomic database of hepatocellular carcinoma revealed aberrant cancer target genes and loci

Exploring the anti-hepatocellular carcinoma effects of Xianglian Pill: Integrating network pharmacology and RNA sequencing via in silico and in vitro studies

BACKGROUND

Liver cancer represents a most common and fatal cancer worldwide. Xianglian Pill (XLP) is an herbal formula holding great promise in clearing heat for treating diseases in an integrative and holistic way. However, due to the complex constituents and multiple targets, the exact molecular mechanisms of action of XLP are still unclear.

PURPOSE

This study is focused on hepatocellular carcinoma (HCC), the most common type of liver cancer. The aim of this study is to develop a fast and efficient model to investigate the anti-HCC effects of XLP, and its underlying mechanisms.

MATERIALS AND METHODS

HepG2, Hep3B, Mahlavu, HuH-7, or Li-7 cells were employed in the studies. The ingredients were analyzed using liquid chromatography tandem mass spectrometry (LC-MS). RNA sequencing combined with network pharmacology was used to elucidate the therapeutic mechanism of XLP in HCC via in silico and in vitro studies. An approach was constructed to improve the accuracy of prediction in network pharmacology by combining big data and omics.

RESULTS

First, we identified 13 potential ingredients in the serum of XLP-administered rats using LC-MS. Then the network pharmacology was performed to predict that XLP demonstrates anti-HCC effects via targeting 94 genes involving in 13 components. Modifying the database thresholds might impact the accuracy of network pharmacology analysis based on RNA sequencing data. For instance, when the matching rate peak is 0.43, the correctness rate peak is 0.85. Moreover, 9 components of XLP and 6 relevant genes have been verified with CCK-8 and RT-qPCR assay, respectively.

CONCLUSION

Based on the crossing studies of RNA sequencing and network pharmacology, XLP was found to improve HCC through multiple targets and pathways. Additionally, the study provides a way to optimize network pharmacology analysis in herbal medicine research.

Decoding the mechanism of andrographolide to combat hepatocellular carcinoma: a network pharmacology integrated molecular docking and dynamics approach

HepatoCellular Carcinoma, being one of the most mortally convoluted malignancy with mounting number of occurrences across the world and being classified as the third most prevalent cause of cancer-associated mortalities and sixth most prevalent neoplasia. The active phytoconstituent andrographolide, derived from Andrographis paniculata is conveyed to reconcile a number of human ailments including various oncologies. However, the molecular mechanism underlying the anti-oncogenic effects of Andrographolide on HCC remains skeptical and unclear, emerging as a budding challenge for researchers and oncologists. The present study intends to analyze the underlying pharmacological mechanism of Andrographolide over HCC, established via assimilated approach of network pharmacology. Herein, the Network pharmacology stratagem was instigated to investigate potential HCC targets. The Andrographolide targets along with HCC targets were extracted from multiple databases. A total of 162 potential overlapping targets among HCC and Andrographolide were obtained and further subjected to gene ontology and Pathway enrichment analysis by employing OmicsBox and DAVID database, respectively. Subsequently, Protein-protein interaction network construction by Cytoscape software identified the top 10 hub nodes which were validated by survival and expression analysis. Further, the results derived from molecular docking and dynamic simulations by CB-Dock2 server and Desmond module (Schrodinger software) indicate ALB, CCND1, HIF1A, TNF, and VEGFA as potential Andrographolide related targets with high binding affinity and promising complex stability. Our findings not only reveal the antioncogenic role of andrographolide but also provide novel insights illuminating the identified targets as scientific foundation for anti-oncogenic clinical application of andrographolide in HCC therapeutics.Communicated by Ramaswamy H. Sarma.

Possible mechanisms associated with immune escape and apoptosis on anti-hepatocellular carcinoma effect of Mu Ji Fang granules

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common digestive system cancers with high mortality rates worldwide. The main ingredients in Mu Ji Fang Granules (MJF) are alkaloids, flavonoids, and polysaccharides. MJF has been used in the clinical treatment of hepatitis, cirrhosis and HCC for more than 30 years. Few previous studies have focused on the mechanism of MJF on tumor immu-nology in the treatment of HCC.

AIM

To explore the mechanism of action of MJF on tumor immunology in the treatment of HCC.

METHODS

The absorbable ingredients of MJF were identified using Molecule Network related to High Performance Liquid Chromatography-Electron Spray Ionization-Time of Flight- Mass Spectrometry, and hub potential anti-HCC targets were screened using network pharmacology and pathway enrichment analysis. Forty male mice were randomly divided into the Blank, Model, and MJF groups (1.8, 5.4, and 10.8 g/kg/d) following 7 d of oral administration. Average body weight gain, spleen and thymus indices were calculated, tumor tissues were stained with hematoxylin and eosin, and Interferon gamma (IFN-γ), Tumor necrosis factor α (TNF-α), Interleukin-2, aspartate aminotransferase, alanine aminotransferase, alpha-fetoprotein (AFP), Fas, and FasL were measured by Enzyme-linked Immunosorbent Assay. Relevant mRNA expression of Bax and Bcl2 was evaluated by Real Time Quantitative PCR (RT-qPCR) and protein expression of Transforming growth factor β1 (TGF-β1) and Mothers against decapentaplegic homolog (SMAD) 4 was assessed by Western blotting. The HepG2 cell line was treated with 10 mg/mL, 20 mg/mL, 30 mg/mL, 40 mg/mL of MJF, and another 3 groups were treated with TGF-β1 inhibitor (LY364947) and different doses of MJF. Relevant mRNA expression of TNF-α, IFN-γ, Bax and Bcl2 was evaluated by RT-qPCR and protein expression of TGF-β1, SMAD2, p-SMAD2, SMAD4, and SMAD7 was assessed by Western blotting.

RESULTS

It was shown that MJF improved body weight gain and tumor inhibition rate in H22 tumor-bearing mice, protected immune organs and liver function, reduced the HCC indicator AFP, affected immunity and apoptosis, and up-regulated the TGF-β1/SMAD signaling pathway, by increasing the relative expression of TGF-β1, SMAD2, p-SMAD2 and SMAD4 and decreasing SMAD7, reducing immune factors TNF-α and IFN-γ, decreasing apoptosis cytokines Fas, FasL and Bcl2/Bax, and inhibiting the effect of LY364947 in HepG2 cells.

CONCLUSION

MJF inhibits HCC by activating the TGF-β1/SMAD signaling pathway, and affecting immune and apoptotic cytokines, which may be due to MJF adjusting immune escape and apoptosis.

Molecular mechanism of Ganji Fang in the treatment of hepatocellular carcinoma based on network pharmacology, molecular docking and experimental verification technology

Background: Hepatocellular carcinoma (HCC) is a malignant tumor harmful to human health. Ganji Fang (GJF) has good clinical efficacy in the treatment of HCC, but its mechanism is still unclear. Objective: The aim of this study was to investigate the mechanism of action of GJF in the treatment of HCC through network pharmacology, molecular docking and in vitro experiments. Methods: A series of network pharmacology methods were used to identify the potential targets and key pathways of GJF in the treatment of HCC. Then, molecular docking technology was used to explore the binding ability of key active ingredients and targets in GJF. Multiple external databases were used to validate the key targets. In in vitro experiments, we performed MTT assays, wound-healing assays, cell cycle assays, apoptosis assays and RT‒qPCR to verify the inhibitory effect of GJF on the Human hepatoma G2 (HepG2) cells. Result: A total of 162 bioactive components and 826 protein targets of GJF were screened, and 611 potential targets of HCC were identified. Finally, 63 possible targets of GJF acting on HCC were obtained. KEGG enrichment analyses showed that the top five pathways were the cell cycle, cellular senescence, p53 signaling pathway, PI3K/Akt signaling pathway, and progesterone-mediated oocyte maturation. Among them, we verified the PI3K/Akt signaling pathway. CCNE1, PKN1, CCND2, CDK4, EPHA2, FGFR3, CDK6, CDK2 and HSP90AAI were enriched in the PI3K/Akt pathway. The molecular docking results showed that the docking scores of eight active components of GJF with the two targets were all less than -5.0, indicating that they had certain binding activity. In vitro cell experiments showed that GJF could inhibit the proliferation and migration of HepG2 cells, block the cell cycle and induce apoptosis of HepG2 cells, which may be related to the PI3K/Akt signaling pathway. In summary, EPHA2 may be an important target of GJF in HCC, and pachymic acid may be an important critical active compound of GJF that exerts anticancer activity. Conclusion: In general, we demonstrated, for the first time, that the molecular mechanism of GJF in HCC may involve induction of G0/G1 phase cycle arrest through inhibition of the PI3K/Akt signaling pathway and promote apoptosis of hepatoma cell lines. This study provides a scientific basis for the subsequent clinical application of GJF and the in-depth study of its mechanism.

Evaluating the Prognostic and Therapeutic Potentials of the Proteasome 26S Subunit, ATPase (PSMC) Family of Genes in Lung Adenocarcinoma: A Database Mining Approach

This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.

Network-Pharmacology-Based Study on Active Phytochemicals and Molecular Mechanism of Cnidium monnieri in Treating Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a malignancy with a high mortality rate globally. For thousands of years, Cnidium monnieri has been used to treat human ailments and is regarded as a veritable treasure trove for drug discovery. This study has investigated the key active phytochemicals and molecular mechanisms of Cnidium monnieri implicated in curing HCC. We utilized the TCMSP database to collect data on the phytochemicals of Cnidium monnieri. The SwissTargetPrediction website tool was used to predict the targets of phytochemicals of Cnidium monnieri. HCC-related genes were retrieved from OncoDB.HCC and Liverome, two liver-cancer-related databases. Using the DAVID bioinformatic website tool, Gene Ontology (GO) and KEGG enrichment analysis were performed on the intersecting targets of HCC-related genes and active phytochemicals in Cnidium monnieri. A network of active phytochemicals and anti-HCC targets was constructed and analyzed using Cytoscape software. Molecular docking of key active phytochemicals was performed with anti-HCC targets using AutoDock Vina (version 1.2.0.). We identified 19 active phytochemicals in Cnidium monnieri, 532 potential targets of these phytochemicals, and 566 HCC-related genes. Results of GO enrichment indicated that Cnidium monnieri might be implicated in affecting gene targets involved in multiple biological processes, such as protein phosphorylation, negative regulation of the apoptotic process, which could be attributed to its anti-HCC effects. KEGG pathway analyses indicated that the PI3K-AKT signaling pathway, pathways in cancer, proteoglycans in cancer, the TNF signaling pathway, VEGF signaling pathway, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance are the main pathways implicated in the anti-HCC effects of Cnidium monnieri. Molecular docking analyses showed that key active phytochemicals of Cnidium monnieri, such as ar-curcumene, diosmetin, and (E)-2,3-bis(2-keto-7-methoxy-chromen-8-yl)acrolein, can bind to core therapeutic targets EGFR, CASP3, ESR1, MAPK3, CCND1, and ERBB2. The results of the present study offer clues for further investigation of the anti-HCC phytochemicals and mechanisms of Cnidium monnieri and provide a basis for developing modern anti-HCC drugs based on phytochemicals in Cnidium monnieri.

Prognostic comparative genes predict targets for sorafenib combination therapies in hepatocellular carcinoma

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Large-scale comparative transcriptomics analysis of hepatocellular carcinoma reveals 664 prognostic comparative HCC (pcHCC) genes.

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pcHCC genes included novel targets with potential utility in sorafenib combination therapies.

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Knockdown of the selective pcHCC genes NCAPG and CENPW downregulated the p38/STAT3 axis to enhance sorafenib combination treatments.

With the increasing incidence and mortality of human hepatocellular carcinoma (HCC) worldwide, revealing innovative targets to improve therapeutic strategies is crucial for prolonging the lives of patients. To identify innovative targets, we conducted a comprehensive comparative transcriptome analysis of 5,410 human HCCs and 974 mouse liver cancers to identify concordantly expressed genes associated with patient survival. Among the 664 identified prognostic comparative HCC (pcHCC) genes, upregulated pcHCC genes were associated with prognostic clinical features, including large tumor size, vascular invasion and late HCC stages. Interestingly, after validating HCC patient prognoses in multiple independent datasets, we matched the 664 aberrant pcHCC genes with the sorafenib-altered genes in TCGA_LIHC patients and found these 664 pcHCC genes were enriched in sorafenib-related functions, such as downregulated xenobiotic and lipid metabolism and upregulated cell proliferation. Therapeutic agents targeting aberrant pcHCC genes presented divergent molecular mechanisms, including suppression of sorafenib-unrelated oncogenic pathways, induction of sorafenib-unrelated ferroptosis, and modulation of sorafenib transportation and metabolism, to potentiate sorafenib therapeutic effects in HCC combination therapy. Moreover, the pcHCC genes NCAPG and CENPW, which have not been targeted in combination with sorafenib treatment, were knocked down and combined with sorafenib treatment, which reduced HCC cell viability based on disruption to the p38/STAT3 axis, thereby hypersensitizing HCC cells. Together, our results provide important resources and reveal that 664 pcHCC genes represent innovative targets suitable for developing therapeutic strategies in combination with sorafenib based on the divergent synergistic mechanisms for HCC tumor suppression.

Echinacea purpurea suppresses the cell survival and metastasis of hepatocellular carcinoma through regulating the PI3K/Akt pathway

Echinacea purpurea (L.) Moench (Ep) is widely used as a kind of dietary supplements, and possesses various pharmacological activities, including immunomodulatory, anti-inflammatory, antitumor effects. However, the inhibitory effects of Ep on the growth and metastasis of hepatocellular carcinoma (HCC) is unclear. Here, the preventive effect and potential mechanism of Ep on HCC was elucidated by systems pharmacology and molecular docking. The results showed that Ep could significantly ameliorate HCC-induced tumor growth and migration in vivo and in vitro. System pharmacology results indicated that 180 genes associated with HCC were regarded as the potential therapeutic targets of Ep, mainly involved in metabolic pathways, cancer pathways, proteoglycans in cancer and PI3K/Akt signaling pathway, which might be a crucial pathway in HCC EMT. A herb-component-target-pathway network was constructed to reveal the interactions between Ep and HCC. Finally, predicted PI3K/Akt pathway was further validated by molecular docking and western blot experiment. This study showed that Ep ameliorates HCC-induced tumor cell survival and migration in mice via the regulation of the PI3K/Akt pathway. Thus, Ep might be a potential new strategy to prevent the growth and metastasis of HCC.

Computational and In Vitro Analysis of Plumbagin's Molecular Mechanism for the Treatment of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor and the second leading cause of cancer-related death in the world. Plumbagin (PL) is a small molecule naphthoquinone compound isolated from Plumbago zeylanica L. that has important anticancer properties, but its mechanism requires further investigation. In this study, we used a comprehensive network pharmacology approach to study the mechanism of action of PL for the treatment of HCC. The method includes the construction of multiple networks; moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify biological processes and signaling pathways. Subsequently, in vitro experiments were performed to verify the predicted molecular mechanisms obtained from the network pharmacology-based analysis. Network pharmacological analysis showed that PL may exert anti-HCC effects by enhancing reactive oxygen species (ROS) production to generate oxidative stress and by regulating the PI3K/Akt and MAPK signaling pathways. In vitro experiments confirmed that PL mainly mediates the production of ROS, regulates the PI3K/Akt and MAPK signaling pathways to promote apoptosis and autophagy, and shows significant therapeutic effects on HCC. In conclusion, our work proposes a comprehensive systems pharmacology approach to explore the potential mechanism of PL for the treatment of HCC.

Network Pharmacology-Based Study on the Mechanism of Scutellariae Radix for Hepatocellular Carcinoma Treatment

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.

Systems Biology and Experimental Model Systems of Cancer

Over the past decade, we have witnessed an increasing number of large-scale studies that have provided multi-omics data by high-throughput sequencing approaches. This has particularly helped with identifying key (epi)genetic alterations in cancers. Importantly, aberrations that lead to the activation of signaling networks through the disruption of normal cellular homeostasis is seen both in cancer cells and also in the neighboring tumor microenvironment. Cancer systems biology approaches have enabled the efficient integration of experimental data with computational algorithms and the implementation of actionable targeted therapies, as the exceptions, for the treatment of cancer. Comprehensive multi-omics data obtained through the sequencing of tumor samples and experimental model systems will be important in implementing novel cancer systems biology approaches and increasing their efficacy for tailoring novel personalized treatment modalities in cancer. In this review, we discuss emerging cancer systems biology approaches based on multi-omics data derived from bulk and single-cell genomics studies in addition to existing experimental model systems that play a critical role in understanding (epi)genetic heterogeneity and therapy resistance in cancer.

Uncovering the Mechanisms of Cryptotanshinone as a Therapeutic Agent Against Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a fatal and dominant form of liver cancer that currently has no effective treatment or positive prognosis. In this study, we explored the antitumor effects of cryptotanshinone (CPT) against HCC and the molecular mechanisms underlying these effects using a systems pharmacology and experimental validation approach. First, we identified a total of 296 CPT targets, 239 of which were also HCC-related targets. We elucidated the mechanisms by which CPT affects HCC through multiple network analysis, including CPT-target network analysis, protein-protein interaction network analysis, target-function network analysis, and pathway enrichment analysis. In addition, we found that CPT induced apoptosis in Huh7 and MHCC97-H ells due to increased levels of cleaved PARP, Bax, and cleaved caspase-3 and decreased Bcl-2 expression. CPT also induced autophagy in HCC cells by increasing LC3-II conversion and the expression of Beclin1 and ATG5, while decreasing the expression of p62/SQSTM1. Autophagy inhibitors (3-methyladenine and chloroquine) enhanced CPT-induced proliferation and apoptosis, suggesting that CPT-induced autophagy may protect HCC cells against cell death. Furthermore, CPT was found to inhibit the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway. Interestingly, activation of PI3K by insulin-like growth factor-I inhibited CPT-induced apoptosis and autophagy, suggesting that the PI3K/AKT/mTOR signaling pathway is involved in both CPT-induced apoptosis and autophagy. Finally, CPT was found to inhibit the growth of Huh7 xenograft tumors. In conclusion, we first demonstrated the antitumor effects of CPT in Huh7 and MHCC97-H cells, both in vitro and in vivo. We elucidated the potential antitumor mechanism of CPT, which involved inducing apoptosis and autophagy by inhibiting the PI3K/Akt/mTOR signaling pathway. Our findings may provide valuable insights into the clinical application of CPT, serving as a potential candidate therapeutic agent for HCC treatment.

MAPRE1 promotes cell cycle progression of hepatocellular carcinoma cells by interacting with CDK2

Targeting cyclin-dependent kinases (CDKs) is a promising method of therapy for cancer. Unfortunately, the efficacy of CDK inhibitors in hepatocellular carcinoma (HCC) is limited, due in part to incomplete understanding of cell cycle progression and a lack of specific biomarkers to adequately identify which patients may be responsive to CDK inhibitors. In the present study, we report that microtubule-associated protein RP/EB family member 1 (MAPRE1), a gene involved in cell cycle and microtubule regulation, is significantly increased in HCC tissue, promotes HCC cell proliferation, enhances in vitro tumorigenesis, and associates with poor prognosis of HCC. We demonstrate that MAPRE1 binds with CDK2, resulting in the hyperphosphorylation of the CDK2 Thr161 residue in HCC cells. Our findings reveal that targeting MAPRE1 might be an effective therapeutic strategy in HCC, and suggest that MAPRE1 expression might provide a promising biomarker to stratify patients with HCC who may benefit from treatment with CDK inhibitors.

Epigenetic Regulation of Differentially Expressed Drug-Metabolizing Enzymes in Cancer

Drug metabolism is a biotransformation process of drugs, catalyzed by drug-metabolizing enzymes (DMEs), including phase I DMEs and phase II DMEs. The aberrant expression of DMEs occurs in the different stages of cancer. It can contribute to the development of cancer and lead to individual variations in drug response by affecting the metabolic process of carcinogen and anticancer drugs. Apart from genetic polymorphisms, which we know the most about, current evidence indicates that epigenetic regulation is also central to the expression of DMEs. This review summarizes differentially expressed DMEs in cancer and related epigenetic changes, including DNA methylation, histone modification, and noncoding RNAs. Exploring the epigenetic regulation of differentially expressed DMEs can provide a basis for implementing individualized and rationalized medication. Meanwhile, it can promote the development of new biomarkers and targets for the diagnosis, treatment, and prognosis of cancer. SIGNIFICANCE STATEMENT: This review summarizes the aberrant expression of DMEs in cancer and the related epigenetic regulation of differentially expressed DMEs. Exploring the epigenetic regulatory mechanism of DMEs in cancer can help us to understand the role of DMEs in cancer progression and chemoresistance. Also, it provides a basis for developing new biomarkers and targets for the diagnosis, treatment, and prognosis of cancer.

dBMHCC: A comprehensive hepatocellular carcinoma (HCC) biomarker database provides a reliable prediction system for novel HCC phosphorylated biomarkers

Hepatocellular carcinoma (HCC), which is associated with an absence of obvious symptoms and poor prognosis, is the second leading cause of cancer death worldwide. Genome-wide molecular biology studies should provide biological insights into HCC development. Based on the importance of phosphorylation for signal transduction, several protein kinase inhibitors have been developed that improve the survival of cancer patients. However, a comprehensive database of HCC-related phosphorylated biomarkers (HCCPMs) and novel HCCPMs prediction platform has been lacking. We have thus constructed the dBMHCC databases to provide expression profiles, phosphorylation and drug information, and evidence type; gathered information on HCC-related pathways and their involved genes as candidate HCC biomarkers; and established a system for evaluating protein phosphorylation and HCC-related biomarkers to improve the reliability of biomarker prediction. The resulting dBMHCC contains 611 notable HCC-related genes, 234 HCC-related pathways, 17 phosphorylation-related motifs and their 255 corresponding protein kinases, 5955 HCC biomarkers, and 1077 predicted HCCPMs. Methionine adenosyltransferase 2B (MAT2B) and acireductone dioxygenase 1 (ADI1), which regulate HCC development and hepatitis C virus infection, respectively, were among the top 10 HCCPMs predicted by dBMHCC. Platelet-derived growth factor receptor alpha (PDGFRA), which had the highest evaluation score, was identified as the target of one HCC drug (Regorafenib), five cancer drugs, and four non-cancer drugs. dBMHCC is an open resource for HCC phosphorylated biomarkers, which supports researchers investigating the development of HCC and designing novel diagnosis methods and drug treatments. Database URL:http://predictor.nchu.edu.tw/dBMHCC.

Interpreting the Pharmacological Mechanisms of Huachansu Capsules on Hepatocellular Carcinoma Through Combining Network Pharmacology and Experimental Evaluation

Hepatocellular carcinoma (HCC) is one of the most fatal cancers across the world. Chinese medicine has been used as adjunctive or complementary therapy for the management of HCC. Huachansu belongs to a class of toxic steroids isolated from toad venom that has important anti-cancer property. This study was aimed to identify the bioactive constituents and molecular targets of Huachansu capsules (HCSCs) for treating HCC using network pharmacology analysis and experimental assays. The major bioactive components of HCSCs were determined using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A series of network pharmacology methods including target prediction, pathway identification, and network establishment were applied to identify the modes of action of HCSCs against HCC. Furthermore, a series of experiments, including MTT, clonogenic assay, 3-D transwell, wound healing assay, as well as flow cytometry, were conducted to verify the inhibitory ability of HCSCs on HCC in vitro. The results showed that 11 chemical components were identified from HCSCs. The network pharmacological analysis showed that there were 82 related anti-HCC targets and 14 potential pathways for these 11 components. Moreover, experimental assays confirmed the inhibitory effects of HCSCs against HCC in vitro. Taken together, our study revealed the synergistic effects of HCSCs on a systematic level, and suggested that HCSCs exhibited anti-HCC effects in a multi-component, multi-target, and multi-pathway manner.

Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a decade with sorafenib as the only approved treatment, multiple new agents have demonstrated efficacy in clinical trials, including the targeted therapies regorafenib, lenvatinib and cabozantinib, the anti-angiogenic antibody ramucirumab, and the immune checkpoint inhibitors nivolumab and pembrolizumab. Although these agents offer new promise to patients with HCC, the optimal choice and sequence of therapies remains unknown and without established biomarkers, and many patients do not respond to treatment. The advances and the decreasing costs of molecular measurement technologies enable profiling of HCC molecular features (such as genome, transcriptome, proteome and metabolome) at different levels, including bulk tissues, animal models and single cells. The release of such data sets to the public enhances the ability to search for information from these legacy studies and provides the opportunity to leverage them to understand HCC mechanisms, rationally develop new therapeutics and identify candidate biomarkers of treatment response. Here, we provide a comprehensive review of public data sets related to HCC and discuss how emerging artificial intelligence methods can be applied to identify new targets and drugs as well as to guide therapeutic choices for improved HCC treatment.

Exploring the active mechanism of berberine against HCC by systematic pharmacology and experimental validation

Berberine (BBR) is the main component of Coptidis rhizoma, the dried rhizome of Coptis chinensis and is a potential plant alkaloid used for the treatment of cancer due to its high antitumor activity. The present study examined the therapeutic potential and molecular mechanism of action of BBR against HCC, using systematic pharmacology combined with a molecular docking approach and experimental validation in vitro. Through systematic pharmacological analysis, it was found that BBR serves a significant role in inhibiting HCC by affecting multiple pathways, especially the PI3K/AKT signaling pathway. Furthermore, the docking approach indicated that the binding of BBR to AKT could lead to the suppression of AKT activity. The present study examined the inhibitory effect of BBR on the PI3K/AKT pathway in HCC and identified that BBR downregulated the expressions of phosphorylated AKT and PI3K in MHCC97‑H and HepG2 cells, inhibiting their growth, cell migration and invasion in a dose‑dependent manner. In addition, inhibition of the AKT pathway by BBR also contributed to cell apoptosis in MHCC97‑H and HepG2 cells. Taken together, the results of the present study suggested that BBR may be a promising antitumor drug for HCC that acts by inhibiting the PI3K/AKT pathway.

Integrating Network Pharmacology and Pharmacological Evaluation for Deciphering the Action Mechanism of Herbal Formula Zuojin Pill in Suppressing Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a kind of complicated disease with an increasing incidence all over the world. A classic Chinese medicine formula, Zuojin pill (ZJP), was shown to exert therapeutic effects on HCC. However, its chemical and pharmacological profiles remain to be elucidated. In the current study, network pharmacology approach was applied to characterize the action mechanism of ZJP on HCC. All compounds were obtained from the corresponding databases, and active compounds were selected according to their oral bioavailability and drug-likeness index. The potential proteins of ZJP were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database and the traditional Chinese medicine integrated database (TCMID), whereas the potential genes of HCC were obtained from OncoDB.HCC and Liverome databases. The potential pathways related to genes were determined by gene ontology (GO) and pathway enrichment analyses. The compound-target and target-pathway networks were constructed. Subsequently, the potential underlying action mechanisms of ZJP on HCC predicted by the network pharmacology analyses were experimentally validated in HCC cellular and orthotopic HCC implantation murine models. A total of 224 components in ZJP were obtained, among which, 42 were chosen as bioactive components. The compound-target network included 32 compounds and 86 targets, whereas the target-pathway network included 70 proteins and 75 pathways. The in vitro and in vivo experiments validated that ZJP exhibited its prominent therapeutic effects on HCC mainly via the regulation of cell proliferation and survival though the EGFR/MAPK, PI3K/NF-κB, and CCND1 signaling pathways. In conclusion, our study suggested combination of network pharmacology prediction with experimental validation may offer a useful tool to characterize the molecular mechanism of traditional Chinese medicine (TCM) ZJP on HCC.

Interpretation of Euphorbia Kansui Stir-Fried with Vinegar Treating Malignant Ascites by a UPLC-Q-TOF/MS Based Rat Serum and Urine Metabolomics Strategy Coupled with Network Pharmacology

Euphorbia kansui stir-fried with vinegar (V-kansui) has promising biological activities toward treating malignant ascites with reduced toxicity compared to crude kansui. But the mechanism concerning promoting the excretion of ascites has not been systematically studied. The purpose of this paper was to investigate the possible mechanism of V-kansui in treating malignant ascites, including metabolic pathways and molecular mechanism using an integrated serum and urine metabolomics coupled with network pharmacology. Serum and urine samples of rats were collected and analyzed by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). A comparison with crude kansui was also made to demonstrate the feasibility of processing. Principle component analysis (PCA) and orthogonal partial least square discriminate analysis (OPLS-DA) were conducted to discriminate the groups, search important variables and reveal the possible pathways. A compound-target-metabolite network was finally constructed to identify the crucial targets to further understand the molecular mechanism. Sixteen significant metabolites contributing to the discrimination of model and control groups were tentatively screened out. They were mainly involved in the arachidonic acid metabolism, steroid hormone biosynthesis and primary bile acid to possibly reduce inflammatory and modulate the renin-angiotensin-aldosterone system to achieve treating malignant ascites. A bio-network starting from the compounds and ending in the metabolites was constructed to elucidate the molecular mechanism. HSP90AA1, ANXA2, PRDX6, PCNA, SOD2 and ALB were identified as the potential key targets that were responsible for the treatment of malignant ascites by the parameter combining the average shortest path length and betweenness centrality. The correlated 17 compounds were considered as the potential active ingredients in V-kansui. In addition, the metabolomics showed that the effect of V-kansui was almost in accordance with crude kansui. These results systematically revealed the mechanism of V-kansui against malignant ascites for the first time using metabolomics coupled with network pharmacology. V-kansui could be a promising safe and therapeutic medicine for the excretion of ascites.

Systematic Investigation of Scutellariae Barbatae Herba for Treating Hepatocellular Carcinoma Based on Network Pharmacology

As the fifth most common type of malignant cancers globally, hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. As a long-time medicinal herb in Traditional Chinese Medicine (TCM), Scutellariae Barbatae Herba (SBH) has also been used for treating various cancers including HCC, but its underlying mechanisms have not been completely clarified. Presently, an innovative network-pharmacology platform was introduced to systematically elucidate the pharmacological mechanisms of SBH against HCC, adopting active ingredients prescreening, target fishing, and network analysis. The results revealed that SBH appeared to work on HCC probably through regulating 4 molecular functions, 20 biological processes, and hitting on 21 candidate targets involved in 40 pathways. By in-depth analysis of the first-ranked signaling pathway and hit genes, only TTR was highly and specially expressed in the liver tissue. TTR might play a crucial role in neutrophil degranulation pathway during SBH against HCC. Hence, TTR might become a therapeutic target of HCC. The study investigated the anti-hepatoma mechanisms of SBH from a holistic perspective, which provided a theoretical foundation for further experimental research and rational clinical application of SBH.

HCCDB: A Database of Hepatocellular Carcinoma Expression Atlas

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.

Bioinformatic analysis and prediction of the function and regulatory network of long non-coding RNAs in hepatocellular carcinoma

Computational analysis and bioinformatics have significantly advanced the ability of researchers to process and analyze biological data. Molecular data from human and model organisms may facilitate drug target validation and identification of biomarkers with increased predictive accuracy. The aim of the present study was to investigate the function of long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) using online databases, and to predict their regulatory mechanism. HCC-associated lncRNAs, their downstream transcription factors and microRNAs (miRNAs/miRs), as well as the HCC-associated target genes, were identified using online databases. HCC-associated lncRNAs, including HOX antisense intergenic RNA (HOTAIR) and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) were selected based on established databases of lncRNAs. The interaction between the HCC-associated lncRNAs and miRNAs (hsa-miR-1, hsa-miR-20a-5p) was predicted using starBase2.0. Signal transducer and activator of transcription 1, hepatocyte nuclear factor 4α (HNF4A), octamer-binding transcription factor 4, Nanog homeobox (NANOG), caudal type homeobox 2 (CDX2), DEAD-box helicase 5, brahma-related gene 1, MYC-associated factor X and MYC proto-oncogene, bHLH transcription factor have been identified as the transcription factors for HOTAIR and MALAT1 using ChIPBase. Additionally, CDX2, HNF4A, NANOG, ETS transcription factor, Jun proto-oncogene and forkhead box protein A1 were identified as the transcription factors for hsa-miR-1 and hsa-miR-20a-5p. CDX2, HNF4A and NANOG were the transcriptional factors in common between the lncRNAs and miRNAs. Cyclin D1, E2F transcription factor 1, epithelial growth factor receptor, MYC, MET proto-oncogene, receptor tyrosine kinase and vascular endothelial growth factor A were identified as target genes for the HCC progression, two of which were also the target genes of hsa-miR-1 and hsa-miR-20a-5p using the miRwalk and OncoDN. HCC databases. Additionally, these target genes may be involved in biological functions, including the regulation of cell growth, cell cycle progression and mitosis, and in disease progression, as demonstrated using DAVID clustering analysis. The present study aimed to predict a regulatory network of lncRNAs in HCC progression using bioinformatics analysis.

Uncovering the anticancer mechanism of Compound Kushen Injection against HCC by integrating quantitative analysis, network analysis and experimental validation

Compound Kushen Injection (CKI) is a Traditional Chinese Medicine (TCM) preparation that has been clinically used in China to treat various types of solid tumours. Although several studies have revealed that CKI can inhibit the proliferation of hepatocellular carcinoma (HCC) cell lines, the active compounds, potential targets and pathways involved in these effects have not been systematically investigated. Here, we proposed a novel idea of “main active compound-based network pharmacology” to explore the anti-cancer mechanism of CKI. Our results showed that CKI significantly suppressed the proliferation and migration of SMMC-7721 cells. Four main active compounds of CKI (matrine, oxymatrine, sophoridine and N-methylcytisine) were confirmed by the integration of ultra-performance liquid chromatography/mass spectrometry (UPLC-MS) with cell proliferation assays. The potential targets and pathways involved in the anti-HCC effects of CKI were predicted by a network pharmacology approach, and some of the crucial proteins and pathways were further validated by western blotting and metabolomics approaches. Our results indicated that CKI exerted anti-HCC effects via the key targets MMP2, MYC, CASP3, and REG1A and the key pathways of glycometabolism and amino acid metabolism. These results provide insights into the mechanism of CKI by combining quantitative analysis of components, network pharmacology and experimental validation.

Loss of 11βHSD1 enhances glycolysis, facilitates intrahepatic metastasis, and indicates poor prognosis in hepatocellular carcinoma

11Beta-hydroxysteroid dehydrogenase type 1 (11βHSD1), converting glucocorticoids from hormonally inactive cortisone to active cortisol, plays an essential role in glucose homeostasis. Accumulating evidence suggests that enhanced glycolytic activity is closely associated with postoperative recurrence and prognosis of hepatocellular carcinoma (HCC). Whether 11βHSD1 contributes to HCC metastasis and recurrence remains unclear. Here we found that expression of 11βHSD1 in human HCC (310 pairs) was frequently decreased compared to the adjacent non-neoplastic liver tissues (ANT), which correlated well with the intrahepatic-metastatic index, serum glycemia, and other malignant clinicopathological characteristics of HCC and predicted poor prognosis. Knockdown of 11βHSD1 in BEL-7402 cells drastically reduced the pH of culture medium and induced cell death. Meanwhile, overexpression of 11βHSD1 in SMMC-7721 HCC cells resulted in repression of cell migration, invasion, angiogenesis, and proliferation in vitro. When transferred into BALB/c nude mice, 11βHSD1 overexpression resulted in decreased intrahepatic metastasis, angiogenesis, and tumor size. F-18-2-fluoro-2-deoxyglucose accumulation assay measured by positron emission tomography elucidated that 11βHSD1 reduced glucose uptake and glycolysis in SMMC-7721 cells in vitro, and intrahepatic metastasis foci and subcutaneous tumor growth in vivo. We showed that 11βHSD1 repressed cell metastasis, angiogenesis and proliferation of HCC by causing disruption of glycolysis via the HIF-1α and c-MYC pathways. In conclusion, 11βHSD1 inhibits the intrahepatic metastasis of HCC via restriction of tumor glycolysis activity and may serve as a prognostic biomarker for patients.

Molecular targets of Chinese herbs: a clinical study of hepatoma based on network pharmacology

Traditional Chinese medicine (TCM) has been used to treat tumors for years and has been demonstrated to be effective. However, the underlying molecular mechanisms of herbs remain unclear. This study aims to ascertain molecular targets of herbs prolonging survival time of patients with advanced hepatocellular carcinoma (HCC) based on network pharmacology, and to establish a research method for accurate treatment of TCM. The survival benefit of TCM treatment with Chinese herbal medicine (CHM) was proved by Kaplan-Meier method and Cox regression analysis among 288 patients. The correlation between herbs and survival time was performed by bivariate correlation analysis. Network pharmacology method was utilized to construct the active ingredient-target networks of herbs that were responsible for the beneficial effects against HCC. Cox regression analysis showed CHM was an independent favorable prognostic factor. The median survival time was 13 months and the 5-year overall survival rates were 2.61% in the TCM group, while there were 6 months, 0 in the non-TCM group. Correlation analysis demonstrated that 8 herbs closely associated with prognosis. Network pharmacology analysis revealed that the 8 herbs regulated multiple HCC relative genes, among which the genes affected proliferation (KRAS, AKT2, MAPK), metastasis (SRC, MMP), angiogenesis (PTGS2) and apoptosis (CASP3) etc.

CoReCG: a comprehensive database of genes associated with colon-rectal cancer

Cancer of large intestine is commonly referred as colorectal cancer, which is also the third most frequently prevailing neoplasm across the globe. Though, much of work is being carried out to understand the mechanism of carcinogenesis and advancement of this disease but, fewer studies has been performed to collate the scattered information of alterations in tumorigenic cells like genes, mutations, expression changes, epigenetic alteration or post translation modification, genetic heterogeneity. Earlier findings were mostly focused on understanding etiology of colorectal carcinogenesis but less emphasis were given for the comprehensive review of the existing findings of individual studies which can provide better diagnostics based on the suggested markers in discrete studies.

Colon Rectal Cancer Gene Database (CoReCG), contains 2056 colon-rectal cancer genes information involved in distinct colorectal cancer stages sourced from published literature with an effective knowledge based information retrieval system. Additionally, interactive web interface enriched with various browsing sections, augmented with advance search facility for querying the database is provided for user friendly browsing, online tools for sequence similarity searches and knowledge based schema ensures a researcher friendly information retrieval mechanism.

Colorectal cancer gene database (CoReCG) is expected to be a single point source for identification of colorectal cancer-related genes, thereby helping with the improvement of classification, diagnosis and treatment of human cancers.

Database URL: lms.snu.edu.in/corecg

dbPHCC: a database of prognostic biomarkers for hepatocellular carcinoma that provides online prognostic modeling

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant cancers with a poor prognosis. For decades, more and more biomarkers were found to effect on HCC prognosis, but these studies were scattered and there were no unified identifiers. Therefore, we built the database of prognostic biomarkers and models for hepatocellular carcinoma (dbPHCC).

METHODS

dbPHCC focuses on biomarkers which were related to HCC prognosis by traditional experiments rather than high-throughput technology. All of the prognostic biomarkers came from literatures issued during 2002 to 2014 in PubMed and were manually selected. dbPHCC collects comprehensive information of candidate biomarkers and HCC prognosis.

RESULTS

dbPHCC mainly contains 567 biomarkers: 323 proteins, 154 genes, and 90 microRNAs. For each biomarker, the reference information, experimental conditions, and prognostic information are shown. Based on two available patient cohort data sets, an exemplified prognostic model was constructed using 15 phosphotransferases in dbPHCC. The web interface does not only provide a full range of browsing and searching, but also provides online analysis tools. dbPHCC is available at http://lifecenter.sgst.cn/dbphcc/

CONCLUSIONS

dbPHCC provides a comprehensive and convenient search and analysis platform for HCC prognosis research.

GENERAL SIGNIFICANCE

dbPHCC is the first database to focus on experimentally verified individual biomarkers, which are related to HCC prognosis. Prognostic markers in dbPHCC have the potential to be therapeutic drug targets and may help in designing new treatments to improve survival of HCC patients. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Network stratification analysis for identifying function-specific network layers

A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (NetSA), to stratify the whole biological network into various function-specific network layers corresponding to particular functions (e.g. KEGG pathways), which transform the network analysis from the gene level to the functional level by integrating expression data, the gene/protein network and gene ontology information altogether. The application of NetSA in yeast and its comparison with a traditional network-partition both suggest that NetSA can more effectively reveal functional implications of network rewiring and extract significant phenotype-related biological processes. Furthermore, for time-series or stage-wise data, the function-specific network layer obtained by NetSA is also shown to be able to characterize the disease progression in a dynamic manner. In particular, when applying NetSA to hepatocellular carcinoma and type 1 diabetes, we can derive functional spectra regarding the progression of the disease, and capture active biological functions (i.e. active pathways) in different disease stages. The additional comparison between NetSA and SPIA illustrates again that NetSA could discover more complete biological functions during disease progression. Overall, NetSA provides a general framework to stratify a network into various layers of function-specific sub-networks, which can not only analyze a biological network on the functional level but also investigate gene rewiring patterns in biological processes.

Up-regulation of histone methyltransferase SETDB1 by multiple mechanisms in hepatocellular carcinoma promotes cancer metastasis

Epigenetic deregulation plays an important role in liver carcinogenesis. Using transcriptome sequencing, we examined the expression of 591 epigenetic regulators in hepatitis B-associated human hepatocellular carcinoma (HCC). We found that aberrant expression of epigenetic regulators was a common event in HCC. We further identified SETDB1 (SET domain, bifurcated 1), an H3K9-specific histone methyltransferase, as the most significantly up-regulated epigenetic regulator in human HCCs. Up-regulation of SETDB1 was significantly associated with HCC disease progression, cancer aggressiveness, and poorer prognosis of HCC patients. Functionally, we showed that knockdown of SETDB1 reduced HCC cell proliferation in vitro and suppressed orthotopic tumorigenicity in vivo. Inactivation of SETDB1 also impeded HCC cell migration and abolished lung metastasis in nude mice. Interestingly, SETDB1 protein was consistently up-regulated in all metastatic foci found in different organs, suggesting that SETDB1 was essential for HCC metastatic progression. Mechanistically, we showed that the frequent up-regulation of SETDB1 in human HCC was attributed to the recurrent SETDB1 gene copy gain at chromosome 1q21. In addition, hyperactivation of specificity protein 1 transcription factor in HCC enhanced SETDB1 expression at the transcriptional level. Furthermore, we identified miR-29 as a negative regulator of SETDB1. Down-regulation of miR-29 expression in human HCC contributed to SETDB1 up-regulation by relieving its post-transcriptional regulation.

CONCLUSION

SETDB1 is an oncogene that is frequently up-regulated in human HCCs; the multiplicity of SETDB1 activating mechanisms at the chromosomal, transcriptional, and posttranscriptional levels together facilitates SETDB1 up-regulation in human HCC.

Sgo1 is a potential therapeutic target for hepatocellular carcinoma

Shugoshin-like protein 1 (Sgo1) is an essential protein in mitosis; it protects sister chromatid cohesion and thereby ensures the fidelity of chromosome separation. We found that the expression of Sgo1 mRNA was relatively low in normal tissues, but was upregulated in 82% of hepatocellular carcinoma (HCC), and correlated with elevated alpha-fetoprotein and early disease onset of HCC. The depletion of Sgo1 reduced cell viability of hepatoma cell lines including HuH7, HepG2, Hep3B, and HepaRG. Using time-lapse microscopy, we showed that hepatoma cells were delayed and ultimately die in mitosis in the absence of Sgo1. In contrast, cell viability and mitotic progression of immortalized cells were not significantly affected. Notably, mitotic cell death induced upon Sgo1 depletion was suppressed upon inhibitions of cyclin-dependent kinase-1 and Aurora kinase-B, or the depletion of mitotic arrest deficient-2. Thus, mitotic cell death induced upon Sgo1 depletion in hepatoma cells is mediated by persistent activation of the spindle assembly checkpoint. Together, these results highlight the essential role of Sgo1 in the maintenance of a proper mitotic progression in hepatoma cells and suggest that Sgo1 is a promising oncotarget for HCC.

Next-generation sequencing and personalized genomic medicine in hepatobiliary malignancies

Liver cancer is a heterogeneous group of tumors characterized by significant molecular and genomic heterogeneity. The advent of powerful genomic technologies has allowed detection of recurrent somatic alterations in liver cancer, including mutations, copy number alterations as well as changes in transcriptomes and epigenomes, with the potential to translate these data into clinically relevant predictive and prognostic factors. In this review, we discuss recent advances in the application of high-throughput genomic technologies in liver cancer and the integration of such cancer genome profiling data, highlighting specific relevant subgroups and explain how this knowledge can be used in translational clinical research, 'basket trials', molecular tumor boards, targeted therapy and for personalized genomic medicine applications.

Bioinformatics and database resources in hepatology

Lately, advances in high-throughput technologies in biomedical research have led to a dramatic increase in the accessibility of molecular insights at multiple biological levels in hepatology. Much of this information is available in publications, but an increasing number of large-scale analyses are currently being stored in databases. Scopes of these databases are very divergent and may range from large, general databases collecting information on almost every known disease, to very specialized databases covering only a specific liver disease or aspect of hepatology. Over recent years, these bioinformatics data repositories have rapidly evolved into an essential aid for molecular hepatology. However, although publicly available through the internet, many of these databases are only known to a few experts. To facilitate access to these resources, the publicly available databases supporting research on liver diseases are summarized in this review.

Pathway and network approaches for identification of cancer signature markers from omics data

The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.

Identification of AKT kinases as unfavorable prognostic factors for hepatocellular carcinoma by a combination of expression profile, interaction network analysis and clinical validation

BACKGROUND & AIM

identification of key markers that differentiate occurrence and progression of hepatocellular carcinoma (HCC) is of great significance to develop novel prognostic factors and improve therapeutic strategies. The aim of this study was to screen novel markers for HCC by combining expression profile, interaction network analysis and clinical validation.

METHODS & RESULTS

HCC significant molecules which were differentially expressed in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). The protein-protein interaction network of HCC significant proteins was constructed and 331 candidate HCC markers were identified by calculating four topological features of the network ('Degree', 'Betweenness', 'Closeness' and 'K-coreness'). According to the enrichment analysis on Gene ontology items and KEGG pathways, these candidate HCC markers were more frequently involved in cellular protein metabolic processes, translational elongation and intracellular signaling cascade, which are associated with cancer development and metastasis. Among 331 candidate HCC markers, the three AKT kinase family members (AKT1-AKT3) were selected for clinical validation by immunohistochemistry analysis using 130 HCC specimens and matched adjacent non-neoplastic liver tissues. Interestingly, the upregulation of AKT1, AKT2 and AKT3 proteins were all significantly associated with tumor aggressiveness and poor prognosis in patients with HCC.

CONCLUSION

this study provided an integrated analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation also indicated that AKT1, AKT2 and AKT3 proteins may all be novel unfavorable prognostic factors for patients with HCC.

Identification of hepatocellular carcinoma related genes with k-th shortest paths in a protein-protein interaction network

Hepatocellular carcinoma (HCC) is the most common type of liver cancer worldwide and one of the deadliest cancers in Asia. But at present, effective targets for HCC clinical therapy are still limited. The "guilt by association" rule suggests that interacting proteins share the same or similar functions and hence may be involved in the same pathway. This assumption can be used to identify disease related genes from protein association networks constructed from existing PPI data. Given the close association between Hepatitis B virus and Hepatitis B which may lead to HCC, here we develop a computational method to identify hepatocellular carcinoma related genes based on k-th shortest paths in the protein-protein interaction (PPI) network (we set k=1, 2 in this study). Finally, we found 33 genes whose p-values were less than 0.05, and most of them have been reported to be involved in HCC tumorigenesis and development. The results also provide a new reference for research into HCC oncogenesis and for development of new strategies for HCC clinical therapies.

Switch of glycolysis to gluconeogenesis by dexamethasone for treatment of hepatocarcinoma

Gluconeogenesis is a fundamental feature of hepatocytes. Whether this gluconeogenic activity is also present in malignant hepatocytes remains unexplored. A better understanding of this biological process may lead to novel therapeutic strategies. Here we show that gluconeogenesis is not present in mouse or human malignant hepatocytes. We find that two critical enzymes 11β-HSD1 and 11β-HSD2 that regulate glucocorticoid activities are expressed inversely in malignant hepatocytes, resulting in the inactivation of endogenous glucocorticoids and the loss of gluconeogenesis. In patients' hepatocarcinoma, the expression of 11β-HSD1 and 11β-HSD2 is closely linked to prognosis and survival. Dexamethasone, an active form of synthesized glucocorticoids, is capable of restoring gluconeogenesis in malignant cells by bypassing the abnormal regulation of 11β-HSD enzymes, leading to therapeutic efficacy against hepatocarcinoma. These findings clarify the molecular basis of malignant hepatocyte loss of gluconeogenesis and suggest new therapeutic strategies.

A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma

Several complex molecular events are involved in tumorigenesis of hepatocellular carcinoma (HCC). The interactions of these molecules may constitute the HCC imbalanced network. Gansui Banxia Tang (GSBXT), as a classic Chinese herbal formula, is a popular complementary and alternative medicine modality for treating HCC. In order to investigate the therapeutic effects and the pharmacological mechanisms of GSBXT on reversing HCC imbalanced network, we in the current study developed a comprehensive systems approach of integrating disease-specific and drug-specific networks, and successfully revealed the relationships of the ingredients in GSBXT with their putative targets, and with HCC significant molecules and HCC related pathway systems for the first time. Meanwhile, further experimental validation also demonstrated the preventive effects of GSBXT on tumor growth in mice and its regulatory effects on potential targets.

Identification of GRB2 and GAB1 coexpression as an unfavorable prognostic factor for hepatocellular carcinoma by a combination of expression profile and network analysis

Aim

To screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation.

Methods

HCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated.

Results

In total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC.

Conclusion

This study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC.

Target genes discovery through copy number alteration analysis in human hepatocellular carcinoma

High-throughput short-read sequencing of exomes and whole cancer genomes in multiple human hepatocellular carcinoma (HCC) cohorts confirmed previously identified frequently mutated somatic genes, such as TP53, CTNNB1 and AXIN1, and identified several novel genes with moderate mutation frequencies, including ARID1A, ARID2, MLL, MLL2, MLL3, MLL4, IRF2, ATM, CDKN2A, FGF19, PIK3CA, RPS6KA3, JAK1, KEAP1, NFE2L2, C16orf62, LEPR, RAC2, and IL6ST. Functional classification of these mutated genes suggested that alterations in pathways participating in chromatin remodeling, Wnt/β-catenin signaling, JAK/STAT signaling, and oxidative stress play critical roles in HCC tumorigenesis. Nevertheless, because there are few druggable genes used in HCC therapy, the identification of new therapeutic targets through integrated genomic approaches remains an important task. Because a large amount of HCC genomic data genotyped by high density single nucleotide polymorphism arrays is deposited in the public domain, copy number alteration (CNA) analyses of these arrays is a cost-effective way to reveal target genes through profiling of recurrent and overlapping amplicons, homozygous deletions and potentially unbalanced chromosomal translocations accumulated during HCC progression. Moreover, integration of CNAs with other high-throughput genomic data, such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models, provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.

Systematic analysis of missing proteins provides clues to help define all of the protein-coding genes on human chromosome 1

Our first proteomic exploration of human chromosome 1 began in 2012 (CCPD 1.0), and the genome-wide characterization of the human proteome through public resources revealed that 32-39% of proteins on chromosome 1 remain unidentified. To characterize all of the missing proteins, we applied an OMICS-integrated analysis of three human liver cell lines (Hep3B, MHCC97H, and HCCLM3) using mRNA and ribosome nascent-chain complex-bound mRNA deep sequencing and proteome profiling, contributing mass spectrometric evidence of 60 additional chromosome 1 gene products. Integration of the annotation information from public databases revealed that 84.6% of genes on chromosome 1 had high-confidence protein evidence. Hierarchical analysis demonstrated that the remaining 320 missing genes were either experimentally or biologically explainable; 128 genes were found to be tissue-specific or rarely expressed in some tissues, whereas 91 proteins were uncharacterized mainly due to database annotation diversity, 89 were genes with low mRNA abundance or unsuitable protein properties, and 12 genes were identifiable theoretically because of a high abundance of mRNAs/RNC-mRNAs and the existence of proteotypic peptides. The relatively large contribution made by the identification of enriched transcription factors suggested specific enrichment of low-abundance protein classes, and SRM/MRM could capture high-priority missing proteins. Detailed analyses of the differentially expressed genes indicated that several gene families located on chromosome 1 may play critical roles in mediating hepatocellular carcinoma invasion and metastasis. All mass spectrometry proteomics data corresponding to our study were deposited in the ProteomeXchange under the identifiers PXD000529, PXD000533, and PXD000535.

Mouse models for liver cancer

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer is the third leading cause of cancer-related cell death in human and the fifth in women worldwide. The incidence of HCC is increasing despite progress in identifying risk factors, understanding disease etiology and developing anti-viral strategies. Therapeutic options are limited and survival after diagnosis is poor. Therefore, better preventive, diagnostic and therapeutic tools are urgently needed, in particular given the increased contribution from systemic metabolic disease to HCC incidence worldwide. In the last three decades, technological advances have facilitated the generation of genetically engineered mouse models (GEMMs) to mimic the alterations frequently observed in human cancers or to conduct intervention studies and assess the relevance of candidate gene networks in tumor establishment, progression and maintenance. Because these studies allow molecular and cellular manipulations impossible to perform in patients, GEMMs have improved our understanding of this complex disease and represent a source of great potential for mechanism-based therapy development. In this review, we provide an overview of the current state of HCC modeling in the mouse, highlighting successes, current challenges and future opportunities.

Differential combinatorial regulatory network analysis related to venous metastasis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world, and metastasis is a significant cause to the high mortality in patients with HCC. However, the molecular mechanism behind HCC metastasis is not fully understood. Study of regulatory networks may help investigate HCC metastasis in the way of systems biology profiling.

Methods

By utilizing both sequence information and parallel microRNA(miRNA) and mRNA expression data on the same cohort of HBV related HCC patients without or with venous metastasis, we constructed combinatorial regulatory networks of non-metastatic and metastatic HCC which contain transcription factor(TF) regulation and miRNA regulation. Differential regulation patterns, classifying marker modules, and key regulatory miRNAs were analyzed by comparing non-metastatic and metastatic networks.

Results

Globally TFs accounted for the main part of regulation while miRNAs for the minor part of regulation. However miRNAs displayed a more active role in the metastatic network than in the non-metastatic one. Seventeen differential regulatory modules discriminative of the metastatic status were identified as cumulative-module classifier, which could also distinguish survival time. MiR-16, miR-30a, Let-7e and miR-204 were identified as key miRNA regulators contributed to HCC metastasis.

Conclusion

In this work we demonstrated an integrative approach to conduct differential combinatorial regulatory network analysis in the specific context venous metastasis of HBV-HCC. Our results proposed possible transcriptional regulatory patterns underlying the different metastatic subgroups of HCC. The workflow in this study can be applied in similar context of cancer research and could also be extended to other clinical topics.

Proinflammatory homeobox gene, ISX, regulates tumor growth and survival in hepatocellular carcinoma

Chronic inflammation drives initiation of hepatocellular carcinoma (HCC), but the underlying mechanisms linking inflammation and tumor formation remain obscure. In this study, we compared the expression of interleukin (IL)-6 and cyclin D1 (CCND1) with the IL-6-induced homeobox gene ISX (intestine-specific homeobox) in 119 paired specimens of HCCs and adjacent normal tissues and also in paired specimens from 11 patients with non-HCCs. In pathologic analysis, ISX exhibited a tumor-specific expression pattern and a high correlation to patient survival time, tumor size, tumor number, and progression stage. Enforced expression of ISX accelerated cell proliferation and tumorigenic activity in hepatoma cells through CCND1 induction. In contrast, short hairpin RNA-mediated attenuation of ISX in hepatoma cells decreased cell proliferation and malignant transformation in vitro and in vivo. A high positive correlation existed in human hepatoma tumors between ISX and CCND1 expression. Together, our results highlight ISX as an important regulator in hepatoma progression with significant potential as a prognostic and therapeutic target in HCCs.

Androgen pathway stimulates microRNA-216a transcription to suppress the tumor suppressor in lung cancer-1 gene in early hepatocarcinogenesis

Deregulation of microRNAs (miRNAs) is common in advanced human hepatocellular carcinoma (HCC); however, the ones involved in early carcinogenesis have not yet been investigated. By examining the expression of 22 HCC-related miRNAs between precancerous and cancerous liver tissues, we found miR-216a and miR-224 were significantly up-regulated, starting from the precancerous stage. Furthermore, the elevation of miR-216a was mainly identified in male patients. To study this gender difference, we demonstrated that pri-miR-216a is activated transcriptionally by the androgen pathway in a ligand-dependent manner and is further enhanced by the hepatitis B virus X protein. The transcription initiation site for pri-miR-216a was delineated, and one putative androgen-responsive element site was identified within its promoter region. Mutation of this site abolished the elevation of pri-miR-216a by the androgen pathway. One target of miR-216a was shown to be the tumor suppressor in lung cancer-1 gene (TSLC1) messenger RNA (mRNA) through the three target sites at its 3' untranslated region. Finally, the androgen receptor level increased in male liver tissues during hepatocarcinogenesis, starting from the precancerous stage, with a concomitant elevation of miR-216a but a decrease of TSLC1.

CONCLUSION

The current study discovered the up-regulation of miRNA-216a by the androgen pathway and a subsequent suppression of TSLC1 as a new mechanism for the androgen pathway in early hepatocarcinogenesis.

Functional and topological properties in hepatocellular carcinoma transcriptome

Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease.