Global gene expression profiling reveals SPINK1 as a potential hepatocellular carcinoma marker

Three-Dimensional Structure of Novel Liver Cancer Biomarker Liver Cancer-Specific Serine Protease Inhibitor Kazal (LC-SPIK) and Its Performance in Clinical Diagnosis of Hepatocellular Carcinoma (HCC)

LC-SPIK is a liver cancer-specific isoform of Serine Protease Inhibitor Kazal and has been proposed as a new biomarker for the detection of HCC given its unique 3D structure, which differs from normal pancreatic SPIK. An ELISA technology based on its unique structure was developed to use LC-SPIK as an effective biomarker for the clinical diagnosis of HCC. AFP, the most widely used biomarker for HCC surveillance currently, suffers from poor clinical performance, especially in the detection of early-stage HCC. In one case-control study, which included 164 HCC patients and 324 controls, LC-SPIK had an AUC of 0.87 compared to only 0.70 for AFP in distinguishing HCC from liver disease controls (cirrhosis, HBV/HCV). LC-SPIK also performed significantly better than AFP for the 81 patients with early-stage HCC (BCLC stage 0 and A), with an AUC of 0.85 compared to only 0.61 for AFP. Cirrhosis is the major risk factor for HCC; about 80% of patients with newly diagnosed HCC have preexisting cirrhosis. LC-SPIK's clinical performance was also studied in HCC patients with viral and non-viral cirrhosis, including cirrhosis caused by metabolic dysfunction-associated steatotic liver disease (MASLD) and alcoholic liver disease (ALD). In a total of 163 viral cirrhosis patients with 93 HCC patients (50 early-stage), LC-SPIK had an AUC of 0.85, while AFP had an AUC of 0.70. For patients with early-stage HCC, LC-SPIK had a similar AUC of 0.83, while AFP had an AUC of only 0.60. For 120 patients with nonviral cirrhosis, including 62 HCC (23 early-stage) patients, LC-SPIK had an AUC of 0.84, while AFP had an AUC of only 0.72. For the 23 patients with early-stage HCC, LC-SPIK had a similar AUC of 0.83, while the AUC for AFP decreased to 0.65. All these results suggest that LC-SPIK exhibits significantly better performance in the detection of HCC than AFP in all etiologies of liver diseases. In addition, LC-SPIK accurately detected the presence of HCC in 71-91% of HCC patients with false-negative AFP test results in viral-associated HCC and non-viral-associated HCC.

Extraordinary variability in gene activation and repression programs during gonadal sex differentiation across vertebrates

Genes involved in gonadal sex differentiation have been traditionally thought to be fairly conserved across vertebrates, but this has been lately questioned. Here, we performed the first comparative analysis of gonadal transcriptomes across vertebrates, from fish to mammals. Our results unambiguously show an extraordinary overall variability in gene activation and repression programs without a phylogenetic pattern. During sex differentiation, genes such as dmrt1, sox9, amh, cyp19a and foxl2 were consistently either male- or female-enriched across species while many genes with the greatest expression change within each sex were not. We also found that downregulation in the opposite sex, which had only been quantified in the mouse model, was also prominent in the rest of vertebrates. Finally, we report 16 novel conserved markers (e.g., fshr and dazl) and 11 signaling pathways. We propose viewing vertebrate gonadal sex differentiation as a hierarchical network, with conserved hub genes such as sox9 and amh alongside less connected and less conserved nodes. This proposed framework implies that evolutionary pressures may impact genes based on their level of connectivity.

A novel diagnostic four-gene signature for hepatocellular carcinoma based on artificial neural network: Development, validation, and drug screening

Background: Hepatocellular carcinoma (HCC) is one of the most common cancers with high mortality in the world. HCC screening and diagnostic models are becoming effective strategies to reduce mortality and improve the overall survival (OS) of patients. Here, we expected to establish an effective novel diagnostic model based on new genes and explore potential drugs for HCC therapy.

Methods: The gene expression data of HCC and normal samples (GSE14811, GSE60502, GSE84402, GSE101685, GSE102079, GSE113996, and GSE45436) were downloaded from the Gene Expression Omnibus (GEO) dataset. Bioinformatics analysis was performed to distinguish two differentially expressed genes (DEGs), diagnostic candidate genes, and functional enrichment pathways. QRT-PCR was used to validate the expression of diagnostic candidate genes. A diagnostic model based on candidate genes was established by an artificial neural network (ANN). Drug sensitivity analysis was used to explore potential drugs for HCC. CCK-8 assay was used to detect the viability of HepG2 under various presentative chemotherapy drugs.

Results: There were 82 DEGs in cancer tissues compared to normal tissue. Protein–protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and infiltrating immune cell analysis were administered and analyzed. Diagnostic-related genes of MT1M, SPINK1, AKR1B10, and SLCO1B3 were selected from DEGs and used to construct a diagnostic model. The receiver operating characteristic (ROC) curves were 0.910 and 0.953 in the training and testing cohorts, respectively. Potential drugs, including vemurafenib, LOXO-101, dabrafenib, selumetinib, Arry-162, and NMS-E628, were found as well. Vemurafenib, dabrafenib, and selumetinib were observed to significantly affect HepG2 cell viability.

Conclusion: The diagnostic model based on the four diagnostic-related genes by the ANN could provide predictive significance for diagnosis of HCC patients, which would be worthy of clinical application. Also, potential chemotherapy drugs might be effective for HCC therapy.

Novel Molecular Targets for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer globally. Indeed, only a few treatments are available, most of which are effective only for the early stages of the disease. Therefore, there is an urgent needing for potential markers for a specifically targeted therapy. Candidate proteins were selected from datasets of The Human Protein Atlas, in order to identify specific tumor-associated proteins overexpressed in HCC samples associated with poor prognosis. Potential epitopes were predicted from such proteins, and homology with peptides derived from viral proteins was assessed. A multiparametric validation was performed, including recognition by PBMCs from HCC-patients and healthy donors, showing a T-cell cross-reactivity with paired epitopes. These results provide novel HCC-specific tumor-associated antigens (TAAs) for immunotherapeutic anti-HCC strategies potentially able to expand pre-existing virus-specific CD8⁺ T cells with superior anticancer efficacy.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

Performance of SPINK1 and SPINK1-based diagnostic model in detection of hepatocellular carcinoma

OBJECTIVES

To identify the SPINK1 or SPINK1-based model as a more reliable biomarker for the diagnosis of hepatocellular carcinoma (HCC).

METHODS

Serum samples and related laboratory parameters were collected from 540 subjects (119 healthy donors, 113 patients with chronic hepatitis B, 122 patients with liver cirrhosis, and 186 patients with HCC). SPINK1 was determined by ELISA assay. Differences in each variable were compared by one-way ANOVA or Kruskal-Wallis test. ROC (receiver operating characteristic) curve analysis was conducted to compare the diagnostic efficiency of alpha-fetoprotein (AFP), SPINK1, and a SPINK1-based combine model constructed by binary Logistic regression.

RESULTS

In detecting HCC using the other three groups as control, ROC curve analysis revealed that SPINK1 alone reached AUC of 0.899 (0.866-0.933), with the sensitivity of 0.812 of and specificity of 0.953. The combined model increased the AUC to 0.945 (0.926-0.964) with the sensitivity and specificity of 0.860 and 0.910, respectively. For AFP, significantly lower AUC (p < 0.0001) was shown, which was 0.695 (0.645-0.745) with the sensitivity and specificity of 0.634 and 0.718, respectively. In discriminating HCC from liver disease control, AUC of SPINK1 was 0.863(0.826-0.894), the sensitivity and specificity were 0.823 and 0.906, respectively. For combined model, the AUC, sensitivity, and specificity were 0.915 (0.884-0.940), 0.863, and 0.916, respectively. For detecting early-stage HCC, SPINK1 and combined model achieved the sensitivity of 0.788 and 0.818, respectively, much higher than AFP of 0.485 (p < 0.05); however, the difference between SPINK1 and combined model was not statistically significant (p = 1).

CONCLUSION

We provided solid evidence for SPINK1 as a robust serological tool for HCC diagnosis.

The role of metabolomics in hepatocellular carcinoma

Background

Hepatocellular carcinoma is the most common primary liver malignancy, with the highest incidence in the developing world, including Egypt. Hepatocellular carcinoma is usually diagnosed in the terminal stage of the disease because of the low sensitivity of the available screening tests. During the process of carcinogenesis, the cellular metabolism is altered to allow cancer cells to adapt to the hypoxic environment and therefore increase anabolic synthesis and survival and avoid the apoptotic death signals. These changes in metabolic status can be tracked by metabolomics analysis.

Main body

Metabolomics is a comprehensive approach for identifying metabolic signatures towards the screening, prediction, and earlier diagnosis of hepatocellular carcinoma with greater efficiency than the conventional diagnostic biomarker. The identification of metabolic changes associated with hepatocellular carcinoma is essential to the understanding of disease pathophysiology and enables better monitoring of high-risk individuals. However, due to the complexity of the metabolic pathways associated with hepatocellular carcinoma, the details of these perturbations are still not adequately characterized. The current status of biomarkers for hepatocellular carcinoma and their insufficiencies and metabolic pathways linked to hepatocellular carcinogenesis are briefly addressed in this mini-review. The review focused on the significantly changed metabolites and pathways associated with hepatocellular carcinoma such as phospholipids, bile acids, amino acids, reactive oxygen species metabolism, and the metabolic changes related to energy production in a cancer cell. The review briefly discusses the sensitivity of metabolomics in the prediction and prognosis of hepatocellular carcinoma and the effect of coexisting multiple etiologies of the disease.

Conclusions

Metabolomics profiling is a potentially promising tool for better predicting, diagnosis, and prognosis of hepatocellular carcinoma.

A hierarchical dynamic model used for investigating feed efficiency and its relationship with hepatic gene expression in APOE*3-Leiden.CETP mice

BACKGROUND

Feed efficiency (FE) is an important trait for livestock and humans. While the livestock industry focuses on increasing FE, in the current obesogenic society it is more of interest to decrease FE. Hence, understanding mechanisms involved in the regulation of FE and particularly how it can be decreased would help tremendously in counteracting the obesity pandemic. However, it is difficult to accurately measure or calculate FE in humans. In this study, we aimed to address this challenge by developing a hierarchical dynamic model based on humanized mouse data.

METHODS

We analyzed existing experimental data derived from 105 APOE*3-Leiden.CETP (E3L.CETP) mice fed a high-fat high-cholesterol (HFHC) diet for 1 (N = 20), 2 (N = 19), 3 (N = 20), and 6 (N = 46) month. We developed an ordinary differential equation (ODE) based model to estimate the FE based on the longitudinal data of body weight and food intake. Since the liver plays an important role in maintaining metabolic homeostasis, we evaluated associations between FE and hepatic gene expression levels. Depending on the feeding duration, we observed different relationships between FE and hepatic gene expression levels.

RESULTS

After 1-month feeding of HFHC diet, we observed that FE was associated with vitamin A metabolism, arachidonic acid metabolism, and the PPAR signaling pathway. After 3- and 6-month feeding of HFHC diet, we observed that FE was associated most strongly with expression levels of Spink1 and H19, genes involved in cell proliferation and glucose metabolism, respectively.

CONCLUSIONS

In conclusion, our analysis suggests that various biological processes such as vitamin A metabolism, hepatic response to inflammation, and cell proliferation associate with FE at different stages of diet-induced obesity.

Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing

Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. co-expressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives.

Fermentable fiber-induced hepatocellular carcinoma in mice recapitulates gene signatures found in human liver cancer

Hepatocellular carcinoma (HCC), the most malignant form of primary liver cancer, is the fourth most prevalent cause of cancer mortality globally. It was recently discovered that the dietary fermentable fiber, inulin, can reprogram the murine liver to favor HCC development in a gut microbiota-dependent manner. Determining the molecular pathways that are either over expressed or repressed during inulin-induced HCC would provide a platform of potential therapeutic targets. In the present study, we have combined analysis of the novel inulin-induced HCC murine model and human HCC samples to identify differentially expressed genes (DEGs) in hepatocarcinogenesis. Hepatic transcriptome profiling revealed that there were 674 DEGs in HCC mice compared to mice safeguarded from HCC. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis uncovered enrichment in ECM-receptor interaction, steroid hormone biosynthesis, PPAR signaling pathway, focal adhesion and protein digestion and absorption during inulin-induced HCC. Tandem mass tag based quantitative, multiplexed proteomic analysis delineated 57 differentially expressed proteins, where the over-expressed proteins were associated with cell adhesion molecules, valine, leucine and isoleucine degradation and ECM-receptor interaction. After obtaining the human orthologs of the mouse genes, we did a comparison analysis to level 3 RNA-seq data found in the Cancer Genome Atlas (TCGA) database, corresponding to human HCC (n = 361) and healthy liver (n = 50) samples. Out of the 549 up-regulated and 68 down-regulated human orthologs identified, 142 genes (137 significantly over-expressed and 5 significantly under-expressed) were associated with human HCC. Using univariate survival analysis, we found 27 over-expressed genes involved in cell-cell adhesion and cell division that were associated with poor HCC patient survival. Overall, the genetic and proteomics signatures highlight potential underlying mechanisms in inulin-induced HCC and support that this murine HCC model is human relevant.

Evaluation of heat stress effects on cellular and transcriptional adaptation of bovine granulosa cells

Background

Heat stress is known to affect follicular dynamics, oocyte maturation, and fertilization by impairing steroidogenic ability and viability of bovine granulosa cell (bGCs). The present study explored the physiological and molecular response of bGCs to different heat stress intensities in-vitro. We exposed the primary bGCs to heat stress (HS) at 39 °C, 40 °C and 41 °C along with control samples (38 °C) for 2 h. To evaluate the impact of heat stress on bGCs, several in vitro cellular parameters including cell apoptosis, intracellular reactive oxygen species (ROS) accumulation and HSP70 kinetics were assessed by flow cytometry, florescence microscopy and western blot, respectively. Furthermore, the ELISA was performed to confirm the 17β-estradiol (E₂) and progesterone (P₄) levels. In addition, the RNA sequencing (RNA-Seq) method was used to get the molecular based response of bGCs to different heat treatments.

Results

Our findings revealed that the HS significantly decreased the cell viability, E₂ and P₄ levels in bGCs, whereas, increased the cellular apoptosis and ROS. Moreover, the RNA-Seq experiments showed that all the treatments (39 °C, 40 °C and 41 °C) significantly regulated many differentially expressed genes (DEGs) i.e. BCL2L1, STAR, CYP11A1, CASP3, SOD2, HSPA13, and MAPK8IP1 and pathways associated with heat stress, apoptosis, steroidogenesis, and oxidative stress. Conclusively, our data demonstrated that the impact of 40 °C treatment was comparatively detrimental for cell viability, apoptosis and ROS accumulation. Notably, a similar trend of gene expression was reported by RT-qPCR for RNA-seq data.

Conclusions

Our study presented a worthy strategy for the first time to characterize the cellular and transcriptomic adaptation of bGCs to heat stress (39, 40 and 41 °C) in-vitro. The results infer that these genes and pathways reported in present study could be useful candidates/indicators for heat stress research in dairy cattle. Moreover, the established model of bGCs to heat stress in the current study provides an appropriate platform to understand the mechanism of how heat-stressed bGCs can affect the quality of oocytes and developing embryo.

High SPINK1 Expression Predicts Poor Prognosis and Promotes Cell Proliferation and Metastasis of Hepatocellular Carcinoma

BACKGROUND

Serine protease inhibitor Kazal type I (SPINK1) is highly expressed and promotes tumor progress in different cancers. This study aimed to evaluate SPINK1's prognostic value and its role in hepatocellular carcinoma (HCC) progress.

METHODS

We use tissue micro-arrays containing 273 tumor and paired para-tumor tissues to evaluate SPINK1's prognostic value in HCC. CCK8 cell proliferation assay, wound healing assays, transwell migration and invasion assays were performed to explore the effect of SPINIK1 on HCC cells. The Cancer Genome Atlas (TCGA) database and Gene set enrichment analysis (GSEA) were used to verify the prognosis value of SPINK1 in HCC and explore the underlying mechanisms.

RESULTS

SPINK1 expression was significantly higher in tumor tissues than paired para-tumor tissues (P < 0.001). Higher SPINK1 expression in tumor was significantly associated with portal vein tumor thrombus formation (P = 0.019) and shorter overall survival (P = 0.029). SPINK1 expression in tumor tissue was an independent predictor for overall survival. SPINK1 increased proliferation (P < 0.001), enhanced migration and invasion ability of HCC cell lines (P < 0.001). GSEA revealed that glycine, serine, threonine and bile acid metabolism may be the underlying mechanism of SPINK1 in HCC.

CONCLUSIONS

In conclusion, high SPINK1 expression is associated with poor prognosis of HCC. SPINK1 promotes proliferation, migration and invasion ability of HCC cells.

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Overexpression of Hepatocyte Chemerin-156 Lowers Tumor Burden in a Murine Model of Diethylnitrosamine-Induced Hepatocellular Carcinoma

The tumor inhibitory potential of the highly active chemerin-156 isoform was described in orthotopic models of hepatocellular carcinoma (HCC). The majority of HCC arises in the fibrotic liver, which was not reproduced in these studies. Here, a potential therapeutic activity of chemerin-156 was evaluated in diethylnitrosamine (DEN)-induced liver cancer, which mimics fibrosis-associated HCC. Mice were infected with adeno-associated virus (AAV) six months after DEN injection to overexpress chemerin-156 in the liver, and animals injected with non-recombinant-AAV served as controls. Three months later, the animals were killed. Both groups were comparable with regard to liver steatosis and fibrosis. Of note, the number of very small tumors was reduced by chemerin-156. Anyhow, the expression of inflammatory and profibrotic genes was similar in larger tumors of control and chemerin-156-AAV-infected animals. Although genes with a role in lipid metabolism, like 3-hydroxy-3-methylglutaryl-coenzym-A--reductase, were overexpressed in tumors of animals with high chemerin-156, total hepatic cholesterol, diacylglycerol and triglyceride levels, and distribution of individual lipid species were normal. Chemerin-156-AAV-infected mice had elevated hepatic and systemic chemerin. Ex vivo activation of the chemerin receptor chemokine-like receptor 1 increased in parallel with serum chemerin, illustrating the biological activity of the recombinant protein. In the tumors, chemerin-155 was the most abundant variant. Chemerin-156 was not detected in tumors of the controls and was hardly found in chemerin-156-AAV infected animals. In conclusion, the present study showed that chemerin-156 overexpression caused a decline in the number of small lesions but did not prevent the growth of pre-existing neoplasms.

Classification of early and late stage liver hepatocellular carcinoma patients from their genomics and epigenomics profiles

Background

Liver Hepatocellular Carcinoma (LIHC) is one of the major cancers worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting the stage of LIHC from the genomic profile of samples.

Methods

The Cancer Genome Atlas (TCGA) dataset of 173 early stage (stage-I), 177 late stage (stage-II, Stage-III and stage-IV) and 50 adjacent normal tissue samples for 60,483 RNA transcripts and 485,577 methylation CpG sites, was extensively analyzed to identify the key transcriptomic expression and methylation-based features using different feature selection techniques. Further, different classification models were developed based on selected key features to categorize different classes of samples implementing different machine learning algorithms.

Results

In the current study, in silico models have been developed for classifying LIHC patients in the early vs. late stage and cancerous vs. normal samples using RNA expression and DNA methylation data. TCGA datasets were extensively analyzed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early vs. late stages and cancer vs. normal samples of LIHC with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC (Matthew’s correlation coefficient) 0.58 with an accuracy of 78.87% on the validation dataset in discrimination of early and late stage. Additionally, the prediction models developed based on 5 RNA transcripts and 5 CpG sites classify LIHC and normal samples with an accuracy of 96–98% and AUC (Area Under the Receiver Operating Characteristic curve) 0.99. Besides, multiclass models also developed for classifying samples in the normal, early and late stage of cancer and achieved an accuracy of 76.54% and AUC of 0.86.

Conclusion

Our study reveals stage prediction of LIHC samples with high accuracy based on the genomics and epigenomics profiling is a challenging task in comparison to the classification of cancerous and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP (http://webs.iiitd.edu.in/raghava/cancerlsp/).

Hepatitis B Virus X Protein-Induced Serine Protease Inhibitor Kazal Type 1 Is Associated with the Progression of HBV-Related Diseases

Objective

Hepatitis B virus (HBV) causes inflammation of the liver and is the leading cause of both liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Serine protease inhibitor Kazal type 1 (SPINK1) is an acute-phase response protein that is overexpressed in liver cancer tissue. This study investigated the clinical value of SPINK1 with regard to the diagnosis of HBV-related diseases and its regulatory mechanism.

Methods

Serum levels of SPINK1 in HBV-infected patients and healthy participants were detected by enzyme-linked immunosorbent assay (ELISA). Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) and western blotting were used to detect differential expression of SPINK1 mRNA and protein in HepG2 and HepG2.2.15 cells. The HBV infectious clone pHBV1.3 and its individual genes were cotransfected into HepG2 cells with the SPINK1 promoter coupled to a luciferase reporter; luciferase activity was measured, and the expression levels of SPINK1 were examined.

Results

Serum SPINK1 levels of HBV-infected patients were significantly higher than those of healthy participants, and the serum levels of SPINK1 in patients who tested positive for HBeAg were significantly higher than those in patients who tested negative for HBeAg. The serum SPINK1 levels of patients with LC or HCC were markedly higher than those of patients with chronic hepatitis. The HBV X protein (HBx) activated the SPINK1 promoter to upregulate expression of SPINK1 at both mRNA and protein levels.

Conclusions

HBV enhances expression of SPINK1 through X. SPINK1 levels are increased during progression of HBV-related diseases and might be utilized as a biomarker for the diagnosis of HBV-related diseases.

HBx-K130M/V131I Promotes Liver Cancer in Transgenic Mice via AKT/FOXO1 Signaling Pathway and Arachidonic Acid Metabolism

Chronic hepatitis B viral (HBV) infection remains a high underlying cause for hepatocellular carcinoma (HCC) worldwide, while the genetic mechanisms behind this remain unclear. This study elucidated the mechanisms contributing to tumor development induced by the HBV X (HBx) gene of predominantly Asian genotype B HBV and its common HBx variants. To compare the potential tumorigenic effects of K130M/V131I (Mut) and wild-type (WT) HBx on HCC, the Sleeping Beauty (SB) transposon system was used to deliver HBx Mut and WT into the livers of fumarylacetoacetate hydrolase (Fah)-deficient mice and in the context of transformation related protein 53 (Trp53) deficiency. From our results, HBx Mut had a stronger tumorigenic effect than its WT variant. Also, inflammation, necrosis, and fibrosis were evident in HBx experimental animals. Reduction of forkhead box O1 (FOXO1) with increased phosphorylation of upstream serine/threonine kinase (AKT) was detected under HBx Mut overexpression. Thus, it is proposed that HBx Mut enhances disease progression by reducing FOXO1 via phosphorylation of AKT. At the metabolomic level, HBx altered the expression of genes that participated in arachidonic acid (AA) metabolism, as a result of inflammation via accumulation of proinflammatory factors such as prostaglandins and leukotriene in liver. Taken together, the increased rate of HCC observed in chronic hepatitis B patients with K130M/V131I-mutated X protein, may be due to changes in AA metabolism and AKT/FOXO1 signaling. IMPLICATIONS: Our findings suggested that HBx-K130M/V131I-mutant variant promoted HCC progression by activating AKT/FOXO1 pathway and inducing stronger inflammation in liver via AA metabolism.

A novel tumor suppressor SPINK5 targets Wnt/β-catenin signaling pathway in esophageal cancer

Esophageal cancer is one of the most common tumor in the world, and the morbidity rate is as high as 100/100 000 in some parts of China. Therefore, it is important and urgent to explore the pathogenesis of esophageal cancer and find new therapeutic targets for esophageal cancer. In this study, we found that a novel tumor suppressor SPINK5 is significantly reduced in the development of esophageal cancer, and is closely related to the pathological differentiation and lymph node metastasis of esophageal cancer via bioinformatics analysis and esophageal cancer tissue array. Further studies have found that SPINK5 is closely related to Wnt/β‐catenin signaling pathway by bioinformatics analysis and western blot. In esophageal cancer cells, SPINK5 overexpression can inhibit Wnt/β‐catenin signaling pathway. Combined with LiCl or MG‐132 treatment, SPINK5 can inhibit GSK3β phosphorylation and promote β‐catenin protein degradation, thus inhibit Wnt/β‐catenin signaling pathway. In vivo study, SPINK5 overexpression can significantly inhibit the growth of esophageal cancer cells. Our study shows that SPINK5 can inhibit the proliferation, migration, and invasion of esophageal cancer cells by inhibiting Wnt/β‐catenin signaling pathway, and thus plays an important role in the development of esophageal cancer, and may serve as a treatment target of esophageal cancer.

The Diagnostic Role of SPINK1 in Differentiating Hepatocellular Carcinoma From Nonmalignant Lesions

BACKGROUND AND AIM

Distinction of small-sized hepatocellular carcinoma (HCC) from dysplastic nodules may be difficult. In addition, distinction of well-differentiated HCC (WD-HCC) from high-grade dysplastic nodule (HGDN) is also difficult in small needle biopsy. We aimed to study serine peptidase inhibitor, Kazal type 1 (SPINK1) immunohistochemical expression in HCC to differentiate it from nonmalignant lesions.

METHODS

This study included 179 specimens from the archival material of Pathology Department, National Liver Institute, Menoufia University, between 2007 and 2014, divided as 93 HCC and 86 nonmalignant lesions. All cases were stained for SPINK1 antibody.

RESULTS

SPINK1 was expressed in 76.3% of HCC cases with a diagnostic accuracy of 79.3%.There was a significant difference between focal nodular hyperplasia and WD-HCC cases regarding mean value of SPINK1 expression (P=0.015). In addition, there was low SPINK1 score in cirrhosis cases compared with WD-HCC. Moreover, there was a high significant difference between WD-HCC and HGDN regarding SPINK1 expression (P=0.001), with 83.3% sensitivity and 84.6% specificity.

CONCLUSIONS

SPINK1 can be used to differentiate between a WD-HCC and a HGDN with high diagnostic validity.

Large-scale analysis reveals a novel risk score to predict overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers.

Materials and methods

One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein–protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. The robustness of this panel was assessed in the GSE14520 cohort. We verified details of the gene expression level of the key molecules through TCGA, GEO, and qPCR and used immunohistochemistry for substantiation in HCC tissues. The methylation states of these genes were also explored.

Results

Ninety-eight genes, consisting of 13 upregulated and 85 downregulated genes, were screened out in three datasets. KEGG and Gene ontology analysis for the DEGs revealed important biological features of each subtype. Protein–protein interaction network analysis was constructed, consisting of 64 nodes and 115 edges. A subset of four genes (SPINK1, TXNRD1, LCAT, and PZP) that formed a prognostic gene expression signature was established from TCGA and validated in GSE14520. Next, the expression details of the four genes were validated with TCGA, GEO, and clinical samples. The expression panels of the four genes were closely related to methylation states.

Conclusion

This study identified a novel four-gene signature biomarker for predicting the prognosis of HCC. The biomarkers may also reveal molecular mechanisms underlying development of the disease and provide new insights into interventional strategies.

Familial hepatocellular carcinoma: 'A model for studying preventive and therapeutic measures'

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide, with more than 80% of cases found in endemic areas of hepatitis B such as Africa or East Asia. A family history of liver cancer increases HCC risk, independently of hepatitis. The combination of family history of liver cancer and hepatitis B/C serum markers is associated with an over 70-fold elevated HCC risk and poor prognosis. Only limited attention has been given to the role of primary genetic factors in HCC, but scattered anecdotal reports have identified familial aggregations of HCC. This article reviewed the literature on familial hepatocellular carcinoma and suggest that familial HCC may be a good model for studying preventive and therapeutic measures.

•

Highest risk for HCC occur when a hereditary component acts in concert with hepatitis B virus.

•

Different single nucleotide polymorphisms affect various biological pathways predisposing other risk factors.

•

More extensive investigation of the genetic hypothesis of HCC and its fibrolamellar variant required.

•

Prevention with neonatal vaccination is better than cure.

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.

Transgenic expression of the RNA binding protein IMP2 stabilizes miRNA targets in murine microsteatosis

Adult expression of IMP2 is often associated with several types of disease and cancer. The RNA binding protein IMP2 binds and stabilizes the IGF2 mRNA as well as hundreds of other transcripts during development. To gain insight into the molecular action of IMP2 and its contribution to disease in context of adult cellular metabolism, we analyze transgenic overexpression of IMP2 in mouse livers, which has been shown to induce a steatosis-like phenotype and enhanced risk to develop hepatocellular carcinoma (HCC). Our data show up-regulation of several HCC marker genes and miRNAs (miR438-3p and miR151-5p). To characterize the impact of miRNAs to their targets, integrative analysis of transcriptome-and miRNAome-dynamics in combination with IMP2 target prediction was carried out. Our analyses show that targets of expressed miRNAs become accumulated in the case that these transcripts have positive IMP2 binding prediction. Therefore, our data indicates that overexpression of IMP2 alters the regulatory capacity of many miRNAs and we conclude that IMP2 competes with miRNAs for binding sites on thousands of transcripts. As a result, our data implicates that overexpression of IMP2 has distinct effects to the regulatory capacity of miRNAs with yet unknown consequences for translational efficiency.

Screening of biomarkers for liver adenoma in low-dose-rate γ-ray-irradiated mice

PURPOSE

Chronic low-dose-rate (20 mGy/day) γ-irradiation increases the incidence of hepatocellular adenomas (HCA) in female B6C3F1 mice. The purpose of this study is to identify potential serum biomarkers for these HCAs by a new approach.

MATERIAL AND METHODS

Microarray analysis were performed to compare the gene expression profiles of HCAs from mice exposed to low-dose-rate γ-rays with those of normal livers from non-irradiated mice. From the differentially expressed genes, those for possibly secretory proteins were selected. Then, the levels of the proteins in sera were analysed by ELISA.

RESULTS

Microarray analysis identified 4181 genes differentially expressed in HCAs (>2.0-fold). From these genes, those for α-fetoprotein (Afp), α-1B-glycoprotein (A1bg) and serine peptidase inhibitor Kazal type-3 (Spink3) were selected as the genes for candidate proteins. ELISA revealed that the levels of Afp and A1bg proteins in sera significantly increased and decreased, respectively, in low-dose-rate irradiated mice with HCAs and also same tendency was observed in human patients with hepatocellular carcinomas.

CONCLUSION

These results indicate that A1bg could be a new serum biomarker for liver tumor. This new approach of using microarray to select genes for secretory proteins is useful for prediction of novel tumor markers in sera.

Gene network analysis reveals a novel 22-gene signature of carbon metabolism in hepatocellular carcinoma

Although much progress has been made in understanding cancer cellular metabolism adaptation, the co-regulations between genes of metabolism and cancer pathways and their interactions remain poorly characterized. Here, we applied gene co-expression network analysis to 1509 metabolic gene expression data generated from 120 HCC and 180 non-tumor human liver tissues by microarray. Our analyses reveal that metabolism genes can be classified into different co-expression modules based on their associations with HCC related traits. The co-regulation mechanism of the carbon metabolism genes in normal liver tissues was interrupted during the processes of carcinogenesis. In parallel, we performed RNAseq analysis of HCC and non-tumor human liver tissues, and identified a unique 22-carbon-metabolism-gene-signature of increased expression. This gene signature was further verified in multiple microarray data sets, and its prognostic value was also proven by HCC patients' survival data from TCGA. Additionally, the tumorigenic function of two representative genes, CS and ACSS1, were validated experimentally by cell growth and spheroid formation assays. The current study provides evidence for the reprogramming of the co-regulation network between carbon metabolism and cancer pathway genes in HCC. In addition, this study also reveals a unique 22-carbon-metabolism-gene-expression-signature in HCC. Strategies targeting these genes may represent new therapeutic approaches for HCC treatment.

Epigenetic alterations in TRAMP mice: epigenome DNA methylation profiling using MeDIP-seq

Purpose

We investigated the genomic DNA methylation profile of prostate cancer in transgenic adenocarcinoma of the mouse prostate (TRAMP) cancer model and to analyze the crosstalk among targeted genes and the related functional pathways.

Methods

Prostate DNA samples from 24-week-old TRAMP and C57BL/6 male mice were isolated. The DNA methylation profiles were analyzed by methylated DNA immunoprecipitation (MeDIP) followed by next-generation sequencing (MeDIP-seq). Canonical pathways, diseases and function and network analyses of the different samples were then performed using the Ingenuity^® Pathway Analysis (IPA) software. Some target genes with significant difference in methylation were selected for validation using methylation specific primers (MSP) and qPCR.

Results

TRAMP mice undergo extensive aberrant CpG hyper- and hypo-methylation. There were 2147 genes with a significant (log2-change ≥ 2) change in CpG methylation between the two groups, as mapped by the IPA software. Among these genes, the methylation of 1105 and 1042 genes was significantly decreased and increased, respectively, in TRAMP prostate tumors. The top associated disease identified by IPA was adenocarcinoma; however, the cAMP response element-binding protein (CREB)-, histone deacetylase 2 (HDAC2)-, glutathione S-transferase pi (GSTP1)- and polyubiquitin-C (UBC)-related pathways showed significantly altered methylation profiles based on the canonical pathway and network analyses. MSP and qPCR results of genes of interests corroborated with MeDIP-seq findings.

Conclusions

This is the first MeDIP-seq with IPA analysis of the TRAMP model to provide novel insight into the genome-wide methylation profile of prostate cancer. Studies on epigenetics, such as DNA methylation, will potentially provide novel avenues and strategies for further development of biomarkers targeted for treatment and prevention approaches for prostate cancer.

Transcriptomic features of primary prostate cancer and their prognostic relevance to castration-resistant prostate cancer

Although various mechanisms of castration-resistant prostate cancer (CRPC) have been discovered, reliable biomarkers for monitoring CRPC progression are lacking. We sought to identify molecules that predict the progression of advanced prostate cancer (AdvPC) into CRPC. The study used primary-site samples (N=45 for next-generation sequencing (NGS); N=243 for real-time polymerase chain reaction) from patients with prostate cancer (PC). Five public databases containing microarray data of AdvPC and CRPC samples were analyzed. The NGS data showed that each progression step in PC associated with distinct gene expression profiles. Androgen receptor (AR) associated with tumorigenesis, advanced progression, and progression into CRPC. Analysis of the paired and unpaired AdvPC and CRPC samples in the NGS cohort showed that 15 genes associated with progression into CRPC. This was validated by cohort-1 and public database analyses. Analysis of the third cohort with AdvPC showed that higher serine peptidase inhibitor, Kazal type 1 (SPINK1) and lower Sp8 transcription factor (SP8) expression associated with progression into CRPC (log-rank test, both P<0.05). Multivariate regression analysis showed that higher SPINK1 (Hazard Ratio (HR)=4.506, 95% confidence intervals (CI)=1.175-17.29, P=0.028) and lower SP8 (HR=0.199, 95% CI=0.063-0.632, P=0.006) expression independently predicted progression into CRPC. Gene network analysis showed that CRPC progression may be mediated through the AR-SPINK1 pathway by a HNF1A-based gene network. Taken together, our results suggest thatSPINK1 and SP8 may be useful for classifying patients with AdvPC who have a higher risk of progressing to CRPC.

Identification of CD14 as a potential biomarker of hepatocellular carcinoma using iTRAQ quantitative proteomics

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors without effective diagnostic biomarkers. This study intended to dynamically analyze serum proteomics in different pathological stages of liver diseases, and discover potential diagnostic biomarkers for early HCC. Patients with hepatitis B virus (HBV) infection, liver cirrhosis (LC), or HCC together with healthy controls (HC) were enrolled. Proteins differentially expressed between groups were screened using isobaric tagging for relative and absolute quantitation (iTRAQ), and promising HCC biomarker candidates were subjected to bioinformatics analysis, including K-means clustering, gene ontology (GO) and string network analysis. Potential biomarkers were validated by Western blotting and enzyme-linked immunosorbent assay (ELISA), and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Finally, 93 differentially expressed proteins were identified, of which 43 differed between HBV and HC, 70 between LC and HC, and 51 between HCC and HC. Expression levels of gelsolin (GELS) and sulfhydryl oxidase 1 (QSOX1) varied with disease state as follows: HC < HBV < LC < HCC. The reverse trend was observed with CD14. These iTRAQ results were confirmed by Western blotting and ELISA. Logistic regression and ROC curve analysis identified the optimal cut-off for alpha-fetoprotein (AFP), CD14 and AFP/CD14 was 191.4 ng/mL (AUC 0.646, 95%CI 0.467-0.825, sensitivity 31.6%, specificity 94.4%), 3.16 ng/mL (AUC 0.760, 95%CI 0.604-0.917, sensitivity 94.7%, specificity 50%) and 0.197 ng/mL (AUC 0.889, 95%CI 0.785-0.993, sensitivity 84.2%, specificity 83.3%) respectively. In conclusion, Assaying CD14 levels may complement AFP measurement for early detection of HCC.

Serine peptidase inhibitor Kazal type 1 (SPINK1) as novel downstream effector of the cadherin-17/β-catenin axis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of liver cancer worldwide. Previously, we reported that cadherin-17 (CDH17) and its related CDH17/β-catenin axis may be responsible for inducing HCC in a subset of patients exhibiting CDH17 over-expression. Here we aimed at obtaining a better understanding of the CDH17-related HCC biology and to obtain further indications for the design of targeted therapies in CDH17 over-expressing HCC patients.

RESULTS

We found that SPINK1 acts as a downstream effector of the CDH17/β-catenin axis in HCC. In addition, we found that SPINK1 expression exhibited a positive correlation with CDH17 expression in human HCCs and was over-expressed in up to 70% of the tumors. We identified SPINK1 as a downstream effector of the CDH17/β-catenin axis using a spectrum of in vitro assays, including gene expression modulation and inhibitor assays, bioinformatics analyses and luciferase reporter assays. These in vitro results were validated in primary human HCCs, including the observation that alteration in β-catenin expression (a core component of the CDH17/β-catenin axis) in tumors affects SPINK1 serum levels in HCC patients. Similar to CDH17, SPINK1 expression in HCC cells was found to be associated with specific tumor-related properties via activating the c-Raf/MEK/ERK pathway.

CONCLUSIONS

Our current data substantiate our knowledge on the role of CDH17 in the biology of HCC and suggest that components of the CDH17/β-catenin axis may serve as therapeutic targets in CDH17 over-expressing HCC patients.

Serine protease inhibitor Kazal type 1 (SPINK1) downregulates E-cadherin and induces EMT of hepatoma cells to promote hepatocellular carcinoma metastasis via the MEK/ERK signaling pathway

OBJECTIVE

To investigate serine protease inhibitor Kazal type 1 (SPINK1) expression and its influence on the prognosis of human hepatocellular carcinoma (HCC) and to explore the underlying molecular mechanisms involved.

METHODS

Altogether 80 patients with HCC who underwent curative resection were followed up for a median of 58.6 months. SPINK1 expression was detected in the primary HCC samples by immunohistochemistry. Its role in tumor invasion and metastasis was evaluated in vitro by gene silencing using a small interfering RNA-mediated approach, recombinant SPINK1 and U0126 (an inhibitor of MEK/ERK). The proteins in the MEK/ERK signaling pathway were detected by Western blot.

RESULTS

Patients with high SPINK1 expression showed poor overall survival (P = 0.0001) and recurrence-free survival (P = 0.001) compared with those with low SPINK1 expression. The suppression of SPINK1 resulted in reduced cell migration and invasion. SPINK1 overexpression was significantly associated with increased cell migration and invasion in vitro. Furthermore, SPINK1 promoted cancer cells motility and epithelial-mesenchymal transition (EMT) via the mitogen-activated protein kinase kinase (MAPK) and extracellular regulated kinase (ERK) pathway, resulting in increased vimentin expression and decreased E-cadherin expression.

CONCLUSION

SPINK1 may be an oncogene that induces EMT via the MEK/ERK pathway and is a potential target for HCC therapy.

Patient-specific hepatocyte-like cells derived from induced pluripotent stem cells model pazopanib-mediated hepatotoxicity

Idiosyncratic drug-induced hepatotoxicity is a major cause of liver damage and drug pipeline failure, and is difficult to study as patient-specific features are not readily incorporated in traditional hepatotoxicity testing approaches using population pooled cell sources. Here we demonstrate the use of patient-specific hepatocyte-like cells (HLCs) derived from induced pluripotent stem cells for modeling idiosyncratic hepatotoxicity to pazopanib (PZ), a tyrosine kinase inhibitor drug associated with significant hepatotoxicity of unknown mechanistic basis. In vitro cytotoxicity assays confirmed that HLCs from patients with clinically identified hepatotoxicity were more sensitive to PZ-induced toxicity than other individuals, while a prototype hepatotoxin acetaminophen was similarly toxic to all HLCs studied. Transcriptional analyses showed that PZ induces oxidative stress (OS) in HLCs in general, but in HLCs from susceptible individuals, PZ causes relative disruption of iron metabolism and higher burden of OS. Our study establishes the first patient-specific HLC-based platform for idiosyncratic hepatotoxicity testing, incorporating multiple potential causative factors and permitting the correlation of transcriptomic and cellular responses to clinical phenotypes. Establishment of patient-specific HLCs with clinical phenotypes representing population variations will be valuable for pharmaceutical drug testing.

Disease monitoring of hepatocellular carcinoma through metabolomics

We elucidate major pathways of hepatocarcinogenesis and accurate diagnostic metabolomic biomarkers of hepatocellular carcinoma (HCC) identified by contemporary HCC metabolomics studies, and delineate a model HCC metabolomics study design. A literature search was carried out on Pubmed for HCC metabolomics articles published in English. All relevant articles were accessed in full text. Major search terms included “HCC”, “metabolomics”, “metabolomics”, “metabonomic” and “biomarkers”. We extracted clinical and demographic data on all patients and consolidated the lead candidate biomarkers, pathways, and diagnostic performance of metabolomic expression patterns reported by all studies in tables. Where reported, we also extracted and summarized the metabolites and pathways most highly associated with the development of cirrhosis in table format. Pathways of lysophospholipid, sphingolipid, bile acid, amino acid, and reactive oxygen species metabolism were most consistently associated with HCC in the cited works. Several studies also elucidate metabolic alterations strongly associated with cirrhosis, with γ-glutamyl peptides, bile acids, and dicarboxylic acids exhibiting the highest capacity for stratifying cirrhosis patients from appropriately matched controls. Collectively, global metabolomic profiles of the referenced works exhibit a promising diagnostic capacity for HCC at a capacity greater than that of conventional diagnostic biomarker alpha-fetoprotein. Metabolomics is a powerful strategy for identifying global metabolic signatures that exhibit potential to be leveraged toward the screening, diagnosis, and management of HCC. A streamlined study design and patient matching methodology may improve concordance among metabolomic datasets in future works.

Genetically Determined Chronic Pancreatitis but not Alcoholic Pancreatitis Is a Strong Risk Factor for Pancreatic Cancer

OBJECTIVE

To study if chronic pancreatitis (CP) is a risk factor for pancreatic cancer.

METHODS

Through a cohort and a case-control study design, CP and other important risk factors including smoking, diabetes, alcohol, obesity, and genetic mutations were studied for their association with pancreatic cancer.

RESULTS

In the cohort study, 402 patients with CP were included. During 3967.74 person-years of exposure, 5 of the 402 patients (4 idiopathic CP, 1 hereditary CP) developed pancreatic cancer after 16.60 ± 3.51 years of CP. The standardized incidence ratio was 121. In the case-control study, 249 pancreatic cancer patients and 1000 healthy controls were included. Of the 249 patients with pancreatic cancer, 24 had underlying idiopathic CP, and none had alcoholic pancreatitis. SPINK1 gene mutation was present in 16 of 26 patients with idiopathic CP who had pancreatic cancer. Multivariable analysis showed CP (odds ratio [OR], 97.67; 95% confidence interval [CI], 12.69-751.36), diabetes (>4 years duration) (OR, 3.05; 95% CI, 1.79-5.18), smoking (OR, 1.93; 95% CI, 1.38-2.69) as significant risk factors for pancreatic cancer. The population attributable risk was 9.41, 9.06, and 9.50 for diabetes, CP, and smoking, respectively.

CONCLUSIONS

Genetically determined CP but not alcoholic CP is a strong risk factor for pancreatic cancer.

Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.

Emerging Roles of SPINK1 in Cancer

BACKGROUND

Tumor-associated trypsin inhibitor (TATI) was originally isolated from the urine of a patient with ovarian cancer. It was later shown to be produced by many other tumors and several normal tissues. It had earlier been isolated from the pancreas and was hence called pancreatic secretory trypsin inhibitor (PSTI). It belongs to a family of protease inhibitors presently called serine peptidase inhibitor Kazal type (SPINK). In the SPINK family TATI/PSTI is SPINK1, which is the name used in this review.

CONTENT

In addition to being a protease inhibitor, SPINK1 also acts as an acute-phase reactant and a growth factor. Furthermore, it has been shown to modulate apoptosis. Overexpression of SPINK1 predicts an unfavorable outcome in several cancers and determination of SPINK1 in serum can be used to identify patients at increased risk of aggressive disease. Thus serum SPINK1 can be used as a prognostic tumor marker. Because SPINK1 acts as a growth factor and an inhibitor of apoptosis in some cancers, it has also been suggested that it can be a therapeutic target in cancer. However, because SPINK1 is the major physiological inhibitor of trypsin, inhibition of SPINK1 may increase the risk of pancreatitis.

SUMMARY

Taking into account the many functions of SPINK1, assessing the role of SPINK1 in cancer has several potentially important clinical applications ranging from a biomarker to a potential new target for cancer therapy.

Familial hepatocellular carcinoma in an endemic area: two case reports

Background

Hepatocellular carcinoma (HCC) usually affects patients aged 50–70 years but earlier onset (25–40 years) may occur in hepatitis B endemic areas. 70–90 % of HCC develop on a background of cirrhosis. However, hepatitis B virus is directly oncogenic and can cause HCC in the absence of cirrhosis. This may represent a major cause of death from late diagnosis in resource-limited areas.

Case presentation

We report a black African family in which clinical diagnosis of HCC was made on two male siblings in the south west region of Cameroon.

Conclusions

The highest risk for HCC may occur in families in which a hereditary component may be acting in concert with hepatitis B virus. In all cases of HCC, it is important to screen all first degree relatives to detect early and asymptomatic disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1366-7) contains supplementary material, which is available to authorized users.

Gene expression and pathway analysis of human hepatocellular carcinoma cells treated with cadmium

Cadmium (Cd) is a toxic and carcinogenic metal naturally occurring in the Earth's crust. A common route of human exposure is via diet and cadmium accumulates in the liver. The effects of Cd exposure on gene expression in human hepatocellular carcinoma (HepG2) cells were examined in this study. HepG2 cells were acutely-treated with 0.1, 0.5, or 1.0 μM Cd for 24h; or chronically-treated with 0.01, 0.05, or 0.1 μM Cd for three weeks and gene expression analysis was performed using Affymetrix GeneChip® Human Gene 1.0 ST Arrays. Acute and chronic exposures significantly altered the expression of 333 and 181 genes, respectively. The genes most upregulated by acute exposure included several metallothioneins. Downregulated genes included the monooxygenase CYP3A7, involved in drug and lipid metabolism. In contrast, CYP3A7 was upregulated by chronic Cd exposure, as was DNAJB9, an anti-apoptotic J protein. Genes downregulated following chronic exposure included the transcriptional regulator early growth response protein 1. Ingenuity Pathway Analysis revealed that the top networks altered by acute exposure were lipid metabolism, small molecule biosynthesis, cell morphology, organization, and development; while top networks altered by chronic exposure were organ morphology, cell cycle, cell signaling, and renal and urological diseases/cancer. Many of the dysregulated genes play important roles in cellular growth, proliferation, and apoptosis, and may be involved in carcinogenesis. In addition to gene expression changes, HepG2 cells treated with cadmium for 24h indicated a reduction in global levels of histone methylation and acetylation that persisted 72 h post-treatment.

Biomarker development, from bench to bedside

This review describes studies performed by our group and other laboratories in the field aimed at development of biomarkers not only for cancer but also for other diseases. The markers covered include tumor-associated trypsin inhibitor (TATI), tumor-associated trypsin (TAT), human chorionic gonadotropin (hCG), prostate-specific antigen (PSA) and their various molecular forms, their biology and diagnostic use. The discovery of TATI was the result of a hypothesis-driven project aimed at finding new biomarkers for ovarian cancer among urinary peptides. TATI has since proved to be a useful prognostic marker for several cancers. Recently, it has been named Serine Peptidase Inhibitor Kazal Type 1 (SPINK1) after being rediscovered by several groups as a tumor-associated peptide by gene expression profiling and proteomic techniques and shown to promote tumor development by stimulating the EGF receptor. To explain why a trypsin inhibitor is strongly expressed in some cancers, research focused on the protease that it inhibited led to the finding of tumor-associated trypsin (TAT). Elevated serum concentrations of TAT-2 were found in some cancer types, but fairly high background levels of pancreatic trypsinogen-2 limited the use of TAT-2 for cancer diagnostics. However, trypsinogen-2 and its complex with α1-protease inhibitor proved to be very sensitive and specific markers for pancreatitis. Studies on hCG were initiated by the need to develop more rapid and sensitive pregnancy tests. These studies showed that serum from men and non-pregnant women contains measurable concentrations of hCG derived from the pituitary. Subsequent development of assays for the subunits of hCG showed that the β subunit of hCG (hCGβ) is expressed at low concentrations by most cancers and that it is a strong prognostic marker. These studies led to the formation of a working group for standardization of hCG determinations and the development of new reference reagents for several molecular forms of hCG. The preparation of intact hCG has been adopted as the fifth international standard by WHO. Availability of several well-defined forms of hCG made it possible to characterize the epitopes of nearly 100 monoclonal antibodies. This will facilitate design of immunoassays with pre-defined specificity. Finally, the discovery of different forms of immunoreactive PSA in serum from a prostate cancer patient led to identification of the complex between PSA and α1-antichymotrypsin, and the use of assays for free and total PSA in serum for improved diagnosis of prostate cancer. Epitope mapping of PSA antibodies and establishment of PSA standards has facilitated establishment well-standardized assays for the various forms of PSA.

DNA methylation and gene expression profiles show novel regulatory pathways in hepatocellular carcinoma

Background

Alcohol is a well-known risk factor for hepatocellular carcinoma (HCC), but the mechanisms underlying the alcohol-related hepatocarcinogenesis are still poorly understood. Alcohol alters the provision of methyl groups within the hepatic one-carbon metabolism, possibly inducing aberrant DNA methylation. Whether specific pathways are epigenetically regulated in alcohol-associated HCC is, however, unknown. The aim of the present study was to investigate the genome-wide promoter DNA methylation and gene expression profiles in non-viral, alcohol-associated HCC. From eight HCC patients undergoing curative surgery, array-based DNA methylation and gene expression data of all annotated genes were analyzed by comparing HCC tissue and homologous cancer-free liver tissue.

Results

After merging the DNA methylation with gene expression data, we identified 159 hypermethylated-repressed, 30 hypomethylated-induced, 49 hypermethylated-induced, and 56 hypomethylated-repressed genes. Notably, promoter DNA methylation emerged as a novel regulatory mechanism for the transcriptional repression of genes controlling the retinol metabolism (ADH1A, ADH1B, ADH6, CYP3A43, CYP4A22, RDH16), iron homeostasis (HAMP), one-carbon metabolism (SHMT1), and genes with a putative, newly identified function as tumor suppressors (FAM107A, IGFALS, MT1G, MT1H, RNF180).

Conclusions

A genome-wide DNA methylation approach merged with array-based gene expression profiles allowed identifying a number of novel, epigenetically regulated candidate tumor-suppressor genes in alcohol-associated hepatocarcinogenesis. Retinol metabolism genes and SHMT1 are also epigenetically regulated through promoter DNA methylation in alcohol-associated HCC.

Due to the reversibility of epigenetic mechanisms by environmental/nutritional factors, these findings may open up to novel interventional strategies for hepatocarcinogenesis prevention in HCC related to alcohol, a modifiable dietary component.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0077-1) contains supplementary material, which is available to authorized users.

Diffusion of information throughout the host interactome reveals gene expression variations in network proximity to target proteins of hepatitis C virus

Hepatitis C virus infection is one of the most common and chronic in the world, and hepatitis associated with HCV infection is a major risk factor for the development of cirrhosis and hepatocellular carcinoma (HCC). The rapidly growing number of viral-host and host protein-protein interactions is enabling more and more reliable network-based analyses of viral infection supported by omics data. The study of molecular interaction networks helps to elucidate the mechanistic pathways linking HCV molecular activities and the host response that modulates the stepwise hepatocarcinogenic process from preneoplastic lesions (cirrhosis and dysplasia) to HCC. Simulating the impact of HCV-host molecular interactions throughout the host protein-protein interaction (PPI) network, we ranked the host proteins in relation to their network proximity to viral targets. We observed that the set of proteins in the neighborhood of HCV targets in the host interactome is enriched in key players of the host response to HCV infection. In opposition to HCV targets, subnetworks of proteins in network proximity to HCV targets are significantly enriched in proteins reported as differentially expressed in preneoplastic and neoplastic liver samples by two independent studies. Using multi-objective optimization, we extracted subnetworks that are simultaneously “guilt-by-association” with HCV proteins and enriched in proteins differentially expressed. These subnetworks contain established, recently proposed and novel candidate proteins for the regulation of the mechanisms of liver cells response to chronic HCV infection.

Transcriptional profiling and co-expression network analysis identifies potential biomarkers to differentiate chronic hepatitis B and the caused cirrhosis

Liver cirrhosis is one of the most common non-neoplastic causes of mortality worldwide. Chronic hepatitis B (CHB) is a major cause of liver cirrhosis in China. To find biomarkers for the diagnosis of CHB caused cirrhosis (HBC), we examined the transcriptional profiling of CHB and HBC. The leukocyte samples of CHB (n = 5) and HBC (n = 5) were analyzed by microarray. The results showed that 2128 mapped genes were differentially expressed between CHB and HBC (fold change ≥ 2.0, p < 0.05). Gene ontology (GO) analysis indicated that these 2128 differentially expressed genes (DEGs) were enriched for immune response and cell formation functions mostly. Moreover, co-expression networks using the k-core algorithm were established to determine the core genes, which may play important roles in the progression of CHB to HBC. There were markedly different gene co-expression patterns in CHB and HBC. We validated the five core genes, CASP1, TGFBI, IFI30, HLA-DMA and PAG1 in CHB (n = 60) and HBC (n = 60) by quantitative RT-PCR. The expression of the five genes were consistent with microarray, and there were statistically significant co-expression patterns of TGFβ1, PAG1 and HLA-DMA mRNA (Pearson correlation coefficient >0.6). Furthermore, we constructed an mRNA panel of TGFBI, IFI30, HLA-DMA and PAG1 (TIPH HBCtest) by means of a logistic regression model, and evaluated the TIPH HBCtest for HBC diagnosis by area under the receiver operating characteristic curve (AUC) analysis, which showed a higher accuracy (AUC = 0.903). This study suggested that there are particular transcriptional profiles, gene co-expression patterns and core genes in CHB and HBC. The TIPH HBC test may be useful in the diagnosis of HBC from CHB.

Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses

OBJECTIVES

To explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively.

METHODS

In both experiments, genes with high value were selected based on a genome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors in the network were identified. Molecular complex detection algorithm was used to obtain sub-networks.

RESULTS

Based on the new model, the top 300 genes were selected. Co-expression network was constructed and transcription factors were identified. We obtained two common genes FCN2 and CXCL14, and two common transcription factors RFX5 and EZH2. In hepatitis B virus experiment, cluster 1 and 3 had the higher value. In cluster 1, ten of the 17 genes and one transcription factor were all reported associated with hepatocellular carcinoma. In cluster 3, transcription factor ESR1 was reported related with hepatocellular carcinoma. In hepatitis C virus experiment, the value of cluster 3 and 4 was higher. In cluster 3, nine genes were reported to play a key role in hepatocellular carcinoma. In cluster 4, there were 5 genes in the 34 genes. To compare the relevance of a node in holding together communicating nodes, centralities based analysis was performed and we obtained some genes with high stress value.

CONCLUSION

The analysis above helped us to understand the pathogenesis of hepatitis B virus and hepatitis C virus associated hepatocellular carcinoma.

Differential mRNA expression profiles between hepatocellular carcinoma and adjacent normal liver tissue

AIM: To identify differentially expressed genes between hepatocellular carcinoma and normal liver tissues and to carry out bioinformatics analysis.

METHODS: Agilent 8×60 K microarray was used to detect the changes of gene expression between hepatocellular carcinoma and adjacent normal liver tissues. Bioinformatics methods were used to identify differentially expressed genes and perform GO pathway analysis. Real-time PCR was applied to verify microarray data.

RESULTS: Microarray analysis screened a total of up-regulated 924 mRNAs and 1770 down-regulated mRNAs in hepatocellular carcinoma tissues compared with the normal tissues. GO pathway analysis demonstrated that these mRNAs are involved in transcription, redox, signal transduction, ion transport, immune response, cell adhesion, and binding functions. The results of real-time PCR were in high concordance with microarray results.

CONCLUSION: Differentially expressed genes identified in this study may be involved in signal transduction, immune response and other key biological processes. These genes may provide new targets for targeted therapy.