CellMinerHCC: a microarray-based expression database for hepatocellular carcinoma cell lines

Prognostic value of S100A4 and Glypican-3 in hepatocellular carcinoma in cirrhotic HCV patients

AIMS

Both S100A4 and Glypican-3 have been known to be engaged in HCC development and progression. This study aimed to evaluate both S100A4 and GPC3 expression in HCC tissues as a prognostic markers.

METHODS

Tissues from 70 patients of HCC in cirrhotic HCV patients were evaluated by immunohistochemistry using antibodies against SA100A4 and GPC3 and compared with tumor-adjacent tissue (controls). All cases were followed for 40 months.

RESULTS

GPC3 was more expressed in HCC (79%) than S100A4 (21%). S100A4 was more significantly expressed in cases showing metastasis, microscopic vascular emboli, necrosis, and grade III tumors. There was no relationship between overall survival and both S100A4 and GPC3. The only significant independent predictor for recurrence was decompensation (OR 3.037), while metastasis was significantly predicted by S100A4 expression (OR 9.63) and necrosis (OR 8.33).

CONCLUSION

S100A4 might be used as a prognostic marker for HCC, while GPC3 is a reliable marker of HCC diagnosis.

Expression and Function of BMP and Activin Membrane-Bound Inhibitor (BAMBI) in Chronic Liver Diseases and Hepatocellular Carcinoma

BAMBI (bone morphogenetic protein and activin membrane-bound inhibitor) is a transmembrane pseudoreceptor structurally related to transforming growth factor (TGF)-β type 1 receptors (TGF-β1Rs). BAMBI lacks a kinase domain and functions as a TGF-β1R antagonist. Essential processes such as cell differentiation and proliferation are regulated by TGF-β1R signaling. TGF-β is the best-studied ligand of TGF-βRs and has an eminent role in inflammation and fibrogenesis. Liver fibrosis is the end stage of almost all chronic liver diseases, such as non-alcoholic fatty liver disease, and at the moment, there is no effective anti-fibrotic therapy available. Hepatic BAMBI is downregulated in rodent models of liver injury and in the fibrotic liver of patients, suggesting that low BAMBI has a role in liver fibrosis. Experimental evidence convincingly demonstrated that BAMBI overexpression is able to protect against liver fibrosis. Chronic liver diseases have a high risk of hepatocellular carcinoma (HCC), and BAMBI was shown to exert tumor-promoting as well as tumor-protective functions. This review article aims to summarize relevant studies on hepatic BAMBI expression and its role in chronic liver diseases and HCC.

The short isoform of PRLR suppresses the pentose phosphate pathway and nucleotide synthesis through the NEK9-Hippo axis in pancreatic cancer

Prolactin binding to the prolactin receptor exerts pleiotropic biological effects in vertebrates. The prolactin receptor (PRLR) has multiple isoforms due to alternative splicing. The biological roles and related signaling of the long isoform (PRLR-LF) have been fully elucidated. However, little is known about the short isoform (PRLR-SF), particularly in cancer development and metabolic reprogramming, a core hallmark of cancer. Here, we reveal the role and underlying mechanism of PRLR-SF in pancreatic ductal adenocarcinoma (PDAC). Methods: A human PDAC tissue array was used to investigate the clinical relevance of PRLR in PDAC. The in vivo implications of PRLR-SF in PDAC were examined in a subcutaneous xenograft model and an orthotopic xenograft model. Immunohistochemistry was performed on tumor tissue obtained from genetically engineered KPC (KrasG12D/+; Trp53R172H/+; Pdx1-Cre) mice with spontaneous tumors. 13C-labeled metabolite measures, LC-MS, EdU incorporation assays and seahorse analyses were used to identify the effects of PRLR-SF on the pentose phosphate pathway and glycolysis. We identified the molecular mechanisms by immunofluorescence, coimmunoprecipitation, proximity ligation assays, chromatin immunoprecipitation and promoter luciferase activity. Public databases (TCGA, GEO and GTEx) were used to analyze the expression and survival correlations of the related genes. Results: We demonstrated that PRLR-SF is predominantly expressed in spontaneously forming pancreatic tumors of genetically engineered KPC mice and human PDAC cell lines. PRLR-SF inhibits the proliferation of PDAC cells (AsPC-1 and BxPC-3) in vitro and tumor growth in vivo. We showed that PRLR-SF reduces the expression of genes in the pentose phosphate pathway (PPP) and nucleotide biosynthesis by activating Hippo signaling. TEAD1, a downstream transcription factor of Hippo signaling, directly regulates the expression of G6PD and TKT, which are PPP rate-limiting enzymes. Moreover, NEK9 directly interacts with PRLR-SF and is the intermediator between PRLR and the Hippo pathway. The PRLR expression level is negatively correlated with overall survival and TNM stage in PDAC patients. Additionally, pregnancy and lactation increase the ratio of PRLR-SF:PRLR-LF in the pancreas of wild-type mice and subcutaneous PDAC xenograft tumors. Conclusion: Our characterization of the relationship between PRLR-SF signaling, the NEK9-Hippo pathway, PPP and nucleotide synthesis explains a mechanism for the correlation between PRLR-SF and metabolic reprogramming in PDAC progression. Strategies to alter this pathway might be developed for the treatment or prevention of pancreatic cancer.

Transcriptomics-Based Drug Repurposing Approach Identifies Novel Drugs against Sorafenib-Resistant Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC), a type of liver cancer, remains a treatment challenge due to late detection and resistance to currently approved drugs. It takes 15–20 years for a single new drug to become FDA approved. The purpose of this study was to expedite identification of novel drugs against drug-resistant HCC. For this, we matched gene expression alterations in resistant HCC with gene expression changes caused by treatment of cancer cells with drugs already FDA approved for other diseases to find the drug that can reverse the resistance-related changes. Among the identified drugs, we validated the growth inhibitory effect of two drugs, identified their mechanism in HCC and, thus, provided proof of concept evidence for validity of this drug repurposing approach with potential for use in personalized medicine.

Abstract

Objective: Hepatocellular carcinoma (HCC) is frequently diagnosed in patients with late-stage disease who are ineligible for curative surgical therapies. The majority of patients become resistant to sorafenib, the only approved first-line therapy for advanced cancer, underscoring the need for newer, more effective drugs. The purpose of this study is to expedite identification of novel drugs against sorafenib resistant (SR)-HCC. Methods: We employed a transcriptomics-based drug repurposing method termed connectivity mapping using gene signatures from in vitro-derived SR Huh7 HCC cells. For proof of concept validation, we focused on drugs that were FDA-approved or under clinical investigation and prioritized two anti-neoplastic agents (dasatinib and fostamatinib) with targets associated with HCC. We also prospectively validated predicted gene expression changes in drug-treated SR Huh7 cells as well as identified and validated the targets of Fostamatinib in HCC. Results: Dasatinib specifically reduced the viability of SR-HCC cells that correlated with up-regulated activity of SRC family kinases, its targets, in our SR-HCC model. However, fostamatinib was able to inhibit both parental and SR HCC cells in vitro and in xenograft models. Ingenuity pathway analysis of fostamatinib gene expression signature from LINCS predicted JAK/STAT, PI3K/AKT, ERK/MAPK pathways as potential targets of fostamatinib that were validated by Western blot analysis. Fostamatinib treatment reversed the expression of genes that were deregulated in SR HCC. Conclusion: We provide proof of concept evidence for the validity of this drug repurposing approach for SR-HCC with implications for personalized medicine.

A New Relational Database Including Clinical Data and Myocardial Perfusion Imaging Findings in Coronary Artery Disease

BACKGROUND

The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging.

METHODS

We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer.

RESULTS

There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate.

CONCLUSION

The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.

KM-express: an integrated online patient survival and gene expression analysis tool for the identification and functional characterization of prognostic markers in breast and prostate cancers

The identification and functional characterization of novel biomarkers in cancer requires survival analysis and gene expression analysis of both patient samples and cell line models. To help facilitate this process, we have developed KM-Express. KM-Express holds an extensive manually curated transcriptomic profile of 45 different datasets for prostate and breast cancer with phenotype and pathoclinical information, spanning from clinical samples to cell lines. KM-Express also contains The Cancer Genome Atlas datasets for 30 other cancer types with matching cell line expression data for 23 of them. We present KM-Express as a hypothesis generation tool for researchers to identify potential new prognostic RNA biomarkers as well as targets for further downstream functional cell-based studies. Specifically, KM-Express allows users to compare the expression level of genes in different groups of patients based on molecular, genetic, clinical and pathological status. Moreover, KM-Express aids the design of biological experiments based on the expression profile of the genes in different cell lines. Thus, KM-Express provides a one-stop analysis from bench work to clinical prospects. We have used this tool to successfully evaluate the prognostic potential of previously published biomarkers for prostate cancer and breast cancer. We believe KM-Express will accelerate the translation of biomedical research from bench to bed.

Database URL: http://ec2-52-201-246-161.compute-1.amazonaws.com/kmexpress/index.php

Multi-color RGB marking enables clonality assessment of liver tumors in a murine xenograft model

We recently introduced red-green-blue (RGB) marking for clonal cell tracking based on individual color-coding. Here, we applied RGB marking to study clonal development of liver tumors. Immortalized, non-tumorigenic human fetal hepatocytes expressing the human telomerase reverse transcriptase (FH-hTERT) were RGB-marked by simultaneous transduction with lentiviral vectors encoding mCherry, Venus, and Cerulean. Multi-color fluorescence microscopy was used to analyze growth characteristics of RGB-marked FH-hTERT in vitro and in vivo after transplantation into livers of immunodeficient mice with endogenous liver damage (uPA/SCID). After initially polyclonal engraftment we observed oligoclonal regenerative nodules derived from transplanted RGB-marked FH-hTERT. Some mice developed monochromatic invasive liver tumors; their clonal origin was confirmed both on the molecular level, based on specific lentiviral-vector insertion sites, and by serial transplantation of one tumor. Vector insertions in proximity to the proto-oncogene MCF2 and the transcription factor MITF resulted in strong upregulation of mRNA expression in the respective tumors. Notably, upregulated MCF2 and MITF expression was also observed in 21% and 33% of 24 human hepatocellular carcinomas analyzed. In conclusion, liver repopulation with RGB-marked FH-hTERT is a useful tool to study clonal progression of liver tumors caused by insertional mutagenesis in vivo and will help identifying genes involved in liver cancer.

A validated, transitional and translational porcine model of hepatocellular carcinoma

Difficult questions are confronting clinicians attempting to improve hepatocellular carcinoma (HCC) outcomes. A large animal model with genetic, anatomical, and physiological similarities to humans is required to transition from mouse models to human clinical trials to address unmet clinical needs. To validate our previously reported inducible porcine cancer model (Oncopig) as a transitional HCC model, Oncopig hepatocyte cultures were transformed using Cre recombinase. The resulting porcine HCC cells (pHCC) expressed oncogenic TP53R167H and KRASG12D, and displayed nuclear pleomorphisms with pale to granular cytoplasm arranged in expanded plates similar to human HCC histopathology. Human HCC transcriptional hallmarks were detected in pHCC cells using RNA-seq, including TERT reactivation, apoptosis evasion, angiogenesis activation, and Wnt signaling activation. Master regulators of gene expression were conserved across Oncopig and 18 human HCC cell lines. pHCC injection into SCID mice resulted in tumors recapitulating human HCC characteristics, including thick trabeculae formation, pseudoacini patterning, and sheets of well-vascularized stroma. Finally, autologous injection of pHCC cells subcutaneously yielded a tumor histologically characterized as Edmondson Steiner (HCC nuclear grade assessment system) grade 2 HCC with trabecular patterning and T-lymphocyte infiltration. These data demonstrate the Oncopig HCC model's utility for improving detection, treatment, and biomarker discovery relevant to human HCC.

Systematic Analysis of Quantitative Logic Model Ensembles Predicts Drug Combination Effects on Cell Signaling Networks

A major challenge in developing anticancer therapies is determining the efficacies of drugs and their combinations in physiologically relevant microenvironments. We describe here our application of "constrained fuzzy logic" (CFL) ensemble modeling of the intracellular signaling network for predicting inhibitor treatments that reduce the phospho-levels of key transcription factors downstream of growth factors and inflammatory cytokines representative of hepatocellular carcinoma (HCC) microenvironments. We observed that the CFL models successfully predicted the effects of several kinase inhibitor combinations. Furthermore, the ensemble predictions revealed ambiguous predictions that could be traced to a specific structural feature of these models, which we resolved with dedicated experiments, finding that IL-1α activates downstream signals through TAK1 and not MEKK1 in HepG2 cells. We conclude that CFL-Q2LM (Querying Quantitative Logic Models) is a promising approach for predicting effective anticancer drug combinations in cancer-relevant microenvironments.

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.

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.

Prolactin prevents hepatocellular carcinoma by restricting innate immune activation of c-Myc in mice

Women are more resistant to hepatocellular carcinoma (HCC) than men despite equal exposure to major risk factors, such as hepatitis B or C virus infection. Female resistance is hormone-dependent, as evidenced by the sharp increase in HCC incidence in postmenopausal women who do not take hormone replacement therapy. In rodent models sex-dimorphic HCC phenotypes are pituitary-dependent, suggesting that sex hormones act via the gonadal-hypophyseal axis. We found that the estrogen-responsive pituitary hormone prolactin (PRL), signaling through hepatocyte-predominant short-form prolactin receptors (PRLR-S), constrained TNF receptor-associated factor (TRAF)-dependent innate immune responses invoked by IL-1β, TNF-α, and LPS/Toll-like receptor 4 (TLR4), but not TRIF-dependent poly(I:C)/TLR3. PRL ubiquitinated and accelerated poststimulatory decay of a "trafasome" comprised of IRAK1, TRAF6, and MAP3K proteins, abrogating downstream activation of c-Myc-interacting pathways, including PI3K/AKT, mTORC1, p38 MAPK, and NF-κB. Consistent with this finding, we documented exaggerated male liver responses to immune stimuli in mice and humans. Tumor promotion through, but regulation above, the level of c-Myc was demonstrated by sex-independent HCC eruption in Alb-Myc transgenic mice. PRL deficiency accelerated liver carcinogenesis in Prl(-/-) mice of both sexes. Conversely, pharmacologic PRL mobilization using the dopamine D2 receptor antagonist domperidone prevented HCC in tumor-prone C3H/HeN males. Viewed together, our results demonstrate that PRL constrains tumor-promoting liver inflammation by inhibiting MAP3K-dependent activation of c-Myc at the level of the trafasome. PRL-targeted therapy may hold promise for reducing the burden of liver cancer in high-risk men and women.

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.