Background & Aims Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disorder in industrialized countries. Mouse models of NAFLD have been used in studies of pathogenesis and ...treatment, and have certain features of the human disease. We performed a systematic transcriptome-wide analysis of liver tissues from patients at different stages of NAFLD progression (ranging from healthy obese individuals to those with steatosis), as well as rodent models of NAFLD, to identify those that most closely resemble human disease progression in terms of gene expression patterns. Methods We performed a systematic evaluation of genome-wide messenger RNA expression using liver tissues collected from mice fed a standard chow diet (controls) and 9 mouse models of NAFLD: mice on a high-fat diet (with or without fructose), mice on a Western-type diet, mice on a methionine- and choline-deficient diet, mice on a high-fat diet given streptozotocin, and mice with disruption of Pten in hepatocytes. We compared gene expression patterns with those of liver tissues from 25 patients with nonalcoholic steatohepatitis (NASH), 27 patients with NAFLD, 15 healthy obese individuals, and 39 healthy nonobese individuals (controls). Liver samples were obtained from patients undergoing liver biopsy for suspected NAFLD or NASH, or during liver or bariatric surgeries. Data sets were analyzed using the limma R-package. Overlap of functional profiles was analyzed by gene set enrichment analysis profiles. Results We found differences between human and mouse transcriptomes to be significantly larger than differences between disease stages or models. Of the 65 genes with significantly altered expression in patients with NASH and 177 genes with significantly altered expression in patients with NAFLD, compared with controls, only 1–18 of these genes also differed significantly in expression between mouse models of NAFLD and control mice. However, expression of genes that regulate pathways associated with the development of NAFLD were altered in some mouse models (such as pathways associated with lipid metabolism). On a pathway level, gene expression patterns in livers of mice on the high-fat diet were associated more closely with human fatty liver disease than other models. Conclusions In comparing gene expression profiles between liver tissues from different mouse models of NAFLD and patients with different stages of NAFLD, we found very little overlap. Our data set is available for studies of pathways that contribute to the development of NASH and NAFLD and selection of the most applicable mouse models ( http://www.nash-profiler.com ).
A genetic basis of hepatocellular carcinoma (HCC) has been well‐established and major signaling pathways, such as p53, Wnt‐signaling, transforming growth factor‐β (TGF‐β) and Ras pathways, have been ...identified to be essential to HCC development. Lately, the family of platelet‐derived growth factors (PDGFs) has shifted to the center of interest. We have reported on spontaneously developing liver fibrosis in PDGF‐B transgenic mice. Since HCC rarely occurs in healthy liver, but dramatically increases at the cirrhosis stage of which liver fibrosis is a preliminary stage, we investigated liver cancer development in chemically induced liver carcinogenesis in these mice. HCC induction was performed by treatment of the mice with diethylnitrosamine and phenobarbital. At an age of 6 months, the tumor development of these animals was analyzed. Not only the development of dysplastic lesions in PDGF‐B transgenic mice was significantly increased but also their malignant transformation to HCC. Furthermore, we were able to establish a key role of PDGF‐B signaling at diverse stages of liver cancer development. Here, we show that development of liver fibrosis is likely through upregulation of TGF‐β receptors by PDGF‐B. Additionally, overexpression of PDGF‐B also leads to an increased expression of β‐catenin as well as vascular endothelial growth factor and platelet endothelial cell adhesion molecule‐1 (PECAM‐1/CD31), all factors with established roles in carcinogenesis. We were able to extend the understanding of key genetic regulators in HCC development by PDGF‐B and decode essential downstream signals.
Multiple activations of individual genes during embryonic liver and HCC development have repeatedly prompted speculations about conserved embryonic signatures driving cancer development. Recently, ...the emerging discussion on cancer stem cells and the appreciation that generally tumors may develop from progenitor cells of diverse stages of cellular differentiation has shed increasing light on the overlapping genetic signatures between embryonic liver development and HCC. However there is still a lack of systematic studies investigating this area. We therefore performed a comprehensive analysis of differentially regulated genetic signaling pathways in embryonic and liver cancer development and investigated their biological relevance.Genetic signaling pathways were investigated on several publically available genome wide microarray experiments on liver development and HCC. Differentially expressed genes were investigated for pathway enrichment or underrepresentation compared to KEGG annotated pathways by Fisher exact evaluation. The comparative analysis of enrichment and under representation of differentially regulated genes in liver development and HCC demonstrated a significant overlap between multiple pathways. Most strikingly we demonstrated a significant overlap not only in pathways expected to be relevant to both conditions such as cell cycle or apoptosis but also metabolic pathways associated with carbohydrate and lipid metabolism. Furthermore, we demonstrated the clinical significance of these findings as unsupervised clustering of HCC patients on the basis of these metabolic pathways displayed significant differences in survival.These results indicate that liver development and liver cancer share similar alterations in multiple genetic signaling pathways. Several pathways with markedly similar patterns of enrichment or underrepresentation of various regulated genes between liver development and HCC are of prognostic relevance in HCC. In particular, the metabolic pathways were identified as novel prognostically relevant players in HCC development.
Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized ...for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies.
Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors.
We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'.
The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.
Microarray studies have successfully shed light on various aspects of the molecular mechanisms behind the development of hepatocellular carcinoma (HCC), such as the identification of novel molecular ...subgroups and the genetic profiles associated with metastasis and venous invasion. These experiments, mainly comprising genome wide profiling, potentially represent the basis of novel targeted therapeutic strategies in HCC. In response, we summarize the multiple reported expression profiles in HCC associated with HCC development, novel subgroups, venous invasion and metastasis.
Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. ...Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary.
We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources.
Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.
Co-regulated genes are not identified in traditional microarray analyses, but may theoretically be closely functionally linked guilt-by-association (GBA), guilt-by-profiling. Thus, bioinformatics ...procedures for guilt-by-profiling/association analysis have yet to be applied to large-scale cancer biology. We analyzed 2158 full cancer transcriptomes from 163 diverse cancer entities in regard of their similarity of gene expression, using Pearson's correlation coefficient (CC). Subsequently, 428 highly co-regulated genes (|CC| ≥ 0.8) were clustered unsupervised to obtain small co-regulated networks. A major subnetwork containing 61 closely co-regulated genes showed highly significant enrichment of cancer bio-functions. All genes except kinesin family member 18B (KIF18B) and cell division cycle associated 3 (CDCA3) were of confirmed relevance for tumor biology. Therefore, we independently analyzed their differential regulation in multiple tumors and found severe deregulation in liver, breast, lung, ovarian and kidney cancers, thus proving our GBA hypothesis. Overexpression of KIF18B and CDCA3 in hepatoma cells and subsequent microarray analysis revealed significant deregulation of central cell cycle regulatory genes. Consistently, RT-PCR and proliferation assay confirmed the role of both genes in cell cycle progression. Finally, the prognostic significance of the identified KIF18B- and CDCA3-dependent predictors (P = 0.01, P = 0.04) was demonstrated in three independent HCC cohorts and several other tumors. In summary, we proved the efficacy of large-scale guilt-by-profiling/association strategies in oncology. We identified two novel oncogenes and functionally characterized them. The strong prognostic importance of downstream predictors for HCC and many other tumors indicates the clinical relevance of our findings.
Supplementary data are available at Bioinformatics online.
Despite multiple publications, molecular signatures predicting the course of hepatocellular carcinoma (HCC) have not yet been integrated into clinical routine decision-making. Given the diversity of ...published signatures, optimal number, best combinations, and benefit of functional associations of genes in prognostic signatures remain to be defined. We investigated a vast number of randomly chosen gene sets (varying between 1 and 10,000 genes) to encompass the full range of prognostic gene sets on 242 transcriptomic profiles of patients with HCC. Depending on the selected size, 4.7 to 23.5% of all random gene sets exhibit prognostic potential by separating patient subgroups with significantly diverse survival. This was further substantiated by investigating gene sets and signaling pathways also resulting in a comparable high number of significantly prognostic gene sets. However, combining multiple random gene sets using “swarm intelligence” resulted in a significantly improved predictability for approximately 63% of all patients. In these patients, approx. 70% of all random 50-gene containing gene sets resulted in equal and stable prediction of survival. For all other patients, a reliable prediction seems highly unlikely for any selected gene set. Using a machine learning and independent validation approach, we demonstrated a high reliability of random gene sets and swarm intelligence in HCC prognosis. Ultimately, these findings were validated in two independent patient cohorts and independent technical platforms (microarray, RNASeq). In conclusion, we demonstrate that using “swarm intelligence” of multiple gene sets for prognosis prediction may not only be superior but also more robust for predictive purposes.
Key messages
Molecular signatures predicting HCC have not yet been integrated into clinical routine
Depending on the selected size, 4.7 to 23.5% of all random gene sets exhibit prognostic potential; independent of the technical platform (microarray, RNASeq)
Using “swarm intelligence” resulted in a significantly improved predictability
In these patients, approx. 70% of all random 50-gene containing gene sets resulted in equal and stable prediction of survival
Overall, “swarm intelligence” is superior and more robust for predictive purposes in HCC
Myeloid cell leukemia‐1 (Mcl‐1) is an antiapoptotic member of the Bcl‐2 protein family. It interacts with proapoptotic Bcl‐2 family members, thereby inhibiting mitochondrial activation and induction ...of apoptosis. Mcl‐1 is essential for embryonal development and the maintenance of B cells, T cells, and hematopoietic stem cells. We have recently shown that induction of Mcl‐1 by growth factors rescues primary human hepatocytes from CD95‐mediated apoptosis. This prompted us to further analyze the relevance of Mcl‐1 for hepatocellular homeostasis. Therefore, we generated a hepatocyte‐specific Mcl‐1 knockout mouse (Mcl‐1flox/flox‐AlbCre). Deletion of Mcl‐1 in hepatocytes results in liver cell damage caused by spontaneous induction of apoptosis. Livers of Mcl‐1flox/flox‐AlbCre mice are smaller compared to control littermates, due to higher apoptosis rates. As a compensatory mechanism, proliferation of hepatocytes is enhanced in the absence of Mcl‐1. Importantly, hepatic pericellular fibrosis occurs in Mcl‐1 negative livers in response to chronic liver damage. Furthermore, Mcl‐1flox/flox‐AlbCre mice are more susceptible to hepatocellular damage induced by agonistic anti‐CD95 antibodies or concanavalin A. Conclusion: The present study provides in vivo evidence that Mcl‐1 is a crucial antiapoptotic factor for the liver, contributing to hepatocellular homeostasis and protecting hepatocytes from apoptosis induction. (HEPATOLOGY 2009.)
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