Individual Case Safety Report Replication: An Analysis of Case Reporting Transmission Networks.

INTRODUCTION: The basis of pharmacovigilance is provided by the exchange of Individual Case Safety Reports (ICSRs) between the recipient of the original report and other interested parties, which include Marketing Authorization Holders (MAHs) and Health Authorities (HAs). Different regulators have different reporting requirements for report transmission. This results in replication of each ICSR that will exist in multiple locations. Adding in the fact that each case will go through multiple versions, different recipients may receive different case versions at different times, potentially influencing patient safety decisions and potentially amplifying or obscuring safety signals inappropriately. OBJECTIVE: The present study aimed to investigate the magnitude of replication, the variability among recipients, and the subsequent divergence across recipients of ICSRs. METHODS: Seven participating TransCelerate Member Companies (MCs) queried their respective safety databases covering a 3-year period and provided aggregate ICSR submission statistics for expedited safety reports to an independent project manager. As measured in the US Food and Drug Administration (FDA)'s Adverse Event Reporting System (FAERS), ICSR volume for these seven MCs makes up approximately 20% of the total case volume. Aggregate metrics were calculated from the company data, specifically: (i) number of ICSR transmissions, (ii) average number of recipients (ANR) per case version transmitted, (iii) a submission selectivity metric, which measures the percentage of recipients not having received all sequential case version numbers, and (iv) percent of common ISCRs residing in two or more MAH databases. RESULTS: The analysis reflects 2,539,802 case versions, distributed through 7,602,678 submissions. The overall mean replication rate is 3.0 submissions per case version. The distribution of the ANR replication measure was observed to be very long-tailed, with a significant fraction of case versions (~ 12.4% of all transmissions) being sent to ten or more HA recipients. Replication is higher than average for serious, unlisted, and literature cases, ranging from 3.5 to 6.1 submissions per version. Within the subset of ICSR versions sent to three recipients, a significant degree of variability in the actual recipients (i.e., HAs) was observed, indicating that there is not one single combination of the same three HAs predominantly receiving an ICSR. Submission selectivity increases with the case version. For case version 6, the range of the submission selectivity for the MAHs ranges from ~ 10% to over 50%, with a median of 30.2%. Within the participating MAHs, the percentage of cases that reside within at least two safety databases is approximately 2% across five databases. Further analysis of the data from three MAHs showed percentages of 13.4%, 15.6%, and 27.9% of ICSRs originating from HAs and any other partners such as other MAHs and other institutions. CONCLUSION: Replication of ICSRs and the variation of available safety information in recipient databases were quantified and shown to be substantial. Our work shows that multiple processors and medical reviewers will likely handle the same original ICSR as a result of replication. Aside from the obvious duplicate work, this phenomenon could conceivably lead to differing clinical assessments and decisions. If replication could be reduced or even eliminated, this would enable more focus on activities with a benefit for patient safety.

Increased liver carcinogenesis and enrichment of stem cell properties in livers of Dickkopf 2 (Dkk2) deleted mice.

Dkk2 a antagonist of the Wnt/ß-catenin-signaling pathway was shown to be silenced in diverse cancers. More recent data indicate that Dkk family members may also possess functions independent of Wnt-signaling during carcinogenesis. The detailed biological function of Dkks and its relevance for liver cancer is unknown. We analyzed the effects of a genetic deletion of Dkk2 (Dkk2-/-) in a hepatocarcinogenesis model using DEN/Phenobarbital. Untreated Dkk2-/- animals, showed considerable atypia with variation of hepatocyte size and chromatin density. In livers of Dkk2-/- mice nodule formation was seen at 9 months of age with focal loss of trabecular architecture and atypical hepatocytes and after DEN induction Dkk2-/- mice developed significantly more liver tumors compared to controls. Whole transcriptome analysis of untreated Dkk2-/- liver tissue revealed a Dkk2-dependent genetic network involving Wnt/ß-Catenin but also multiple additional oncogenic factors, such as e.g. Pdgf-b, Gdf-15 and Hnf4a. Dkk2-/- tumor cells showed a significant deregulation of stemness genes associated with enhanced colony forming properties. Integration of the Dkk2-/- signature into human data was strongly associated with patients survival. Dkk2 deletion results in alterations of liver morphology leading to an increased frequency of liver cancer. The associated genetic changes included factors not primarily related to Wnt/ß-Catenin-signaling and correlated with the clinical outcome of HCC-patients.

Translating bioinformatics in oncology: guilt-by-profiling analysis and identification of KIF18B and CDCA3 as novel driver genes in carcinogenesis.

MOTIVATION: 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 INFORMATION: Supplementary data are available at Bioinformatics online.

To biopsy or not to biopsy: evaluation of a large German cohort of patients with abnormal liver tests of unknown etiology.

BACKGROUND AND AIMS: Despite increasingly sensitive and accurate blood tests to detect liver disease, liver biopsy remains very useful in patients with atypical clinical features and abnormal liver tests of unknown etiology. The aim was to determine those elevated laboratory liver parameters that cause the clinician to order a biopsy, and whether laboratory tests are associated with pathological findings on histology. METHODS: 504 patients with unclear hepatopathy, admitted to the outpatient clinic of a university hospital between 2007 and 2010, were analyzed with respect to laboratory results, clinical data, and the results of liver biopsies. RESULTS: Aspartate aminotransferase (AST) and glutamate dehydrogenase (GLDH) levels above the normal range significantly increased the likelihood of recommending a liver biopsy by 81% [OR with 95% CI 1.81 (1.21-2.71), p = 0.004] and 159% [OR with 95% CI 2.59 (1.70-3.93), p < 0.001], respectively. AST values above normal were associated with fibrosis (63 vs. 40% for normal AST, p = 0.010). Elevated ferritin levels pointed to a higher incidence of steatosis (48 vs. 10% for normal ferritin, p < 0.001) and inflammation (87 vs. 62% for normal ferritin, p = 0.004). CONCLUSIONS: Our results indicate that elevated AST and GLDH were associated with a greater likelihood of recommending liver biopsy. Elevated AST and ferritin levels were associated with steatosis, inflammation and fibrosis on liver biopsies. Thus, AST and ferritin may be useful non-invasive predictors of liver pathology in patients with unclear hepatopathy.

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

BACKGROUND & AIMS: Therapeutic options for hepatocellular carcinoma (HCC) still remain limited. Development of gene targeted therapies is a promising option. A better understanding of the underlying molecular biology is gained in in vitro experiments. However, even with targeted manipulation of gene expression varying treatment responses were observed in diverse HCC cell lines. Therefore, information on gene expression profiles of various HCC cell lines may be crucial to experimental designs. To generate a publicly available database containing microarray expression profiles of diverse HCC cell lines. METHODS: Microarray data were analyzed using an individually scripted R program package. Data were stored in a PostgreSQL database with a PHP written web interface. Evaluation and comparison of individual cell line expression profiles are supported via public web interface. RESULTS: This database allows evaluation of gene expression profiles of 18 HCC cell lines and comparison of differential gene expression between multiple cell lines. Analysis of commonly regulated genes for signaling pathway enrichment and interactions demonstrates a liver tumor phenotype with enrichment of major cancer related KEGG signatures like 'cancer' and 'inflammatory response'. Further molecular associations of strong scientific interest, e.g. 'lipid metabolism', were also identified. CONCLUSIONS: We have generated CellMinerHCC (http://www.medicalgenomics.org/cellminerhcc), a publicly available database containing gene expression data of 18 HCC cell lines. This database will aid in the design of in vitro experiments in HCC research, because the genetic specificities of various HCC cell lines will be considered.

Sirtuin-6-dependent genetic and epigenetic alterations are associated with poor clinical outcome in hepatocellular carcinoma patients.

UNLABELLED: Sirtuin 6 (SIRT6) is a member of the sirtuin family of NAD+-dependent deacetylases. Genetic deletion of Sirt6 in mice results in a severe degenerative phenotype with impaired liver function and premature death. The role of SIRT6 in development and progression of hepatocellular carcinoma is currently unknown. We first investigated SIRT6 expression in 153 primary human liver cancers and in normal and cirrhotic livers using microarray analysis. SIRT6 was significantly down-regulated in both cirrhotic livers and cancer. A Sirt6 knockout (KO) gene expression signature was generated from primary hepatoctyes isolated from 3-week-old Sirt6-deficient animals. Sirt6-deficient hepatocytes showed up-regulation of established hepatocellular carcinoma (HCC) biomarkers alpha-fetoprotein (Afp), insulin-like growth factor 2 (Igf2), H19, and glypican-3. Furthermore, decreased SIRT6 expression was observed in hepatoma cell lines that are known to be apoptosis-insensitive. Re-expression of SIRT6 in HepG2 cells increased apoptosis sensitivity to CD95-stimulation or chemotherapy treatment. Loss of Sirt6 was characterized by oncogenic changes, such as global hypomethylation, as well as metabolic changes, such as hypoglycemia and increased fat deposition. The hepatocyte-specific Sirt6-KO signature had a prognostic impact and was enriched in patients with poorly differentiated tumors with high AFP levels as well as recurrent disease. Finally, we demonstrated that the Sirt6-KO signature possessed a predictive value for tumors other than HCC (e.g., breast and lung cancer). CONCLUSION: Loss of SIRT6 induces epigenetic changes that may be relevant to chronic liver disease and HCC development. Down-regulation of SIRT6 and genes dysregulated by loss of SIRT6 possess oncogenic effects in hepatocarcinogenesis. Our data demonstrate that deficiency in one epigenetic regulator predisposes a tumorigenic phenotype that ultimately has relevance for outcome of HCC and other cancer patients.

CellLineNavigator: a workbench for cancer cell line analysis.

The CellLineNavigator database, freely available at http://www.medicalgenomics.org/celllinenavigator, is a web-based workbench for large scale comparisons of a large collection of diverse cell lines. It aims to support experimental design in the fields of genomics, systems biology and translational biomedical research. Currently, this compendium holds genome wide expression profiles of 317 different cancer cell lines, categorized into 57 different pathological states and 28 individual tissues. To enlarge the scope of CellLineNavigator, the database was furthermore closely linked to commonly used bioinformatics databases and knowledge repositories. To ensure easy data access and search ability, a simple data and an intuitive querying interface were implemented. It allows the user to explore and filter gene expression, focusing on pathological or physiological conditions. For a more complex search, the advanced query interface may be used to query for (i) differentially expressed genes; (ii) pathological or physiological conditions; or (iii) gene names or functional attributes, such as Kyoto Encyclopaedia of Genes and Genomes pathway maps. These queries may also be combined. Finally, CellLineNavigator allows additional advanced analysis of differentially regulated genes by a direct link to the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources.

Genetic signatures shared in embryonic liver development and liver cancer define prognostically relevant subgroups in HCC.

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.

Identification of RARRES1 as a core regulator in liver fibrosis.

Genetic factors contribute to progression and modulation of hepatic fibrosis. High throughput genomics/transcriptomics approaches aiming at identifying key regulators of fibrosis development are tainted with the difficulty of separating essential biological "driver" from modifier genes. We applied a comparative transcriptomics approach and investigated fibrosis development in different organs to identify overlapping expression changes, since these genes may be part of core pathways in fibrosis development. Gene expression was analysed on publicly available microarray data from liver, lung and kidney fibrosis. RARRES1, AGER and S100A2 were differentially regulated in all fibrosis experiments. RARRES1 was extensively analysed by means of advanced bioinformatics analyses and functional studies. Microarray and Western Blot analysis of a standard liver fibrosis model (CCl(4)) demonstrated an early induction of RARRES1 mRNA and protein expression. In addition, quantitative RT-PCR in tissue samples from patients with advanced liver fibrosis showed higher expression as compared to non-fibrotic biopsies. Microarray analysis of RARRES1 overexpressing cells identified an enrichment of a major signature associated with fibrosis. Furthermore, RARRES1 expression increased during in vitro activation of hepatic stellate cells. To further verify the pro-fibrogenic role across organs, we demonstrated an increase in RARRES1 expression in a rat lung fibrosis model induced by adenoviral TGF-ß1 induction. We have performed a comparative transcriptomics analysis in order to identify core pathways of liver fibrogenesis, confirmed a candidate gene and enlightened the up- and downstream mechanisms of its action leading to fibrosis across organs and species.

RNA-Seq Atlas--a reference database for gene expression profiling in normal tissue by next-generation sequencing.

MOTIVATION: Next-generation sequencing technology enables an entirely new perspective for clinical research and will speed up personalized medicine. In contrast to microarray-based approaches, RNA-Seq analysis provides a much more comprehensive and unbiased view of gene expression. Although the perspective is clear and the long-term success of this new technology obvious, bioinformatics resources making these data easily available especially to the biomedical research community are still evolving. RESULTS: We have generated RNA-Seq Atlas, a web-based repository of RNA-Seq gene expression profiles and query tools. The website offers open and easy access to RNA-Seq gene expression profiles and tools to both compare tissues and find genes with specific expression patterns. To enlarge the scope of the RNA-Seq Atlas, the data were linked to common functional and genetic databases, in particular offering information on the respective gene, signaling pathway analysis and evaluation of biological functions by means of gene ontologies. Additionally, data were linked to several microarray gene profiles, including BioGPS normal tissue profiles and NCI60 cancer cell line expression data. Our data search interface allows an integrative detailed comparison between our RNA-Seq data and the microarray information. This is the first database providing data mining tools and open access to large scale RNA-Seq expression profiles. Its applications will be versatile, as it will be beneficial in identifying tissue specific genes and expression profiles, comparison of gene expression profiles among diverse tissues, but also systems biology approaches linking tissue function to gene expression changes. AVAILABILITY AND IMPLEMENTATION: http://medicalgenomics.org/rna_seq_atlas.

The functional cancer map: a systems-level synopsis of genetic deregulation in cancer.

BACKGROUND: 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. METHODS: 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. RESULTS: 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'. CONCLUSION: 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-based gene expression analysis of hepatocellular carcinoma.

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.

Library of molecular associations: curating the complex molecular basis of liver diseases.

BACKGROUND: 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. RESULTS: 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. CONCLUSION: Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.

A systems biology perspective on cholangiocellular carcinoma development: focus on MAPK-signaling and the extracellular environment.

BACKGROUND/AIMS: Multiple genes have been implicated in cholangiocellular carcinoma (CCC) development. However, the overall neoplastic risk is likely associated with a much lower number of critical physiological pathways. METHODS: To investigate this hypothesis, we extracted all published genetic associations for the development of CCC from PubMed (genetic association studies, but also studies associating genes and CCC in general, i.e. functional studies in cell lines, genetic studies in humans, knockout mice etc.) and integrated CCC microarray data. RESULTS: We demonstrated the MAPK pathway was consistently enriched in CCC. Comparing our data to genetic associations in HCC often successfully treated by a multityrosine kinase inhibitor, sorafenib, we demonstrated a similar overrepresentation of MAPK. In contrast, most cancer-related genetic studies focusing on genes related to transcription and cell cycle control, we consistently found genes coding for products in the extracellular environment to be significantly enriched. Thus, CCC must be regarded as developing in the context of an altered extracellular environment. CONCLUSIONS: Our study suggests the liver microenvironment holds essential functions and structures key to CCC progression. Furthermore, we identified the MAPK signaling pathway consistently enriched, pointing towards a critical role in CCC development. These data may provide a rationale for treatment of CCC with sorafenib.

Genome-wide analysis of factors regulating gene expression in liver.

In recent decades, multiple individual genes have been studied with respect to their level of expression in liver tissue and in many cases substantial progress has been made in identifying individual factors promoting gene expression in liver. However, the overall picture is still undefined and general rules or factors regulating gene expression in liver have not yet been established. Thus, a genome-wide screen for factors regulating gene expression in liver is of high interest, as it may reveal common regulatory mechanisms for most genes highly expressed in liver. These factors represent potential new targets in liver disease associated with differential gene expression. Using a novel bioinformatics approach, we have performed a genome-wide, bioinformatic screen to identify genetic factors regulating gene expression in liver. As the expression of an individual gene is generally driven by its promoter activity, we compared the level of expression to individual promoter sequences. Expression data of 15,704 individual genes in 12 tissues were obtained from a normal tissue microarray dataset. The genes were subsequently divided into two groups, according to whether or not their highest expression level was found in liver tissue. Scanning 1000 bp upstream of the transcription start of each individual gene and using the PromoterScan algorithm, we were able to identify a total of 7042 promoters containing a total of 241,984 transcription factors. To eliminate the possibility that currently unknown transcription factors may be crucial to liver expression regulation, we investigated all possible nucleotide combinations of 8 bp and 10 bp which we reasoned may serve as novel binding sites for transcription factors. In both screens we did not detect any significant, biologically relevant differences in numbers of transcription factors and binding sites between the two groups. Furthermore, we excluded possible differences in distribution of TATA-boxes or CpG islands as well as differences in nucleotide composition of RNA sequences or amino acid composition of transcribed protein sequences. We conclude that the existence of central, superordinated regulatory factors in liver gene expression is unlikely and that expression of individual genes in liver is more likely to be dependent on individual combinations of regulating factors for each gene.

Current bioinformatics tools in genomic biomedical research (Review).

On the advent of a completely assembled human genome, modern biology and molecular medicine stepped into an era of increasingly rich sequence database information and high-throughput genomic analysis. However, as sequence entries in the major genomic databases currently rise exponentially, the gap between available, deposited sequence data and analysis by means of conventional molecular biology is rapidly widening, making new approaches of high-throughput genomic analysis necessary. At present, the only effective way to keep abreast of the dramatic increase in sequence and related information is to apply biocomputational approaches. Thus, over recent years, the field of bioinformatics has rapidly developed into an essential aid for genomic data analysis and powerful bioinformatics tools have been developed, many of them publicly available through the World Wide Web. In this review, we summarize and describe the basic bioinformatics tools for genomic research such as: genomic databases, genome browsers, tools for sequence alignment, single nucleotide polymorphism (SNP) databases, tools for ab initio gene prediction, expression databases, and algorithms for promoter prediction.

Actin binding LIM protein 3 (abLIM3).

LIM domain proteins were demonstrated to play key roles in various biological processes such as embryonic development, cell lineage determination, and cancer differentiation. Actin binding LIM protein 1 (abLIM1) was reported to be localized in a genomic region often deleted in human cancers and suggested to be involved in axon guidance. Recently, existence of a second family member was reported, actin binding LIM protein 2. By means of computational biology and comparative genomics, we now characterized an additional, third member of the actin binding LIM protein subgroup, actin binding LIM protein 3 (abLIM3). The human mRNA sequence was previously annotated as differentially regulated in hepatoblastoma compared to normal livers. Conservation of key structural features of abLIM1 and abLIM2, four LIM domains and a VHD domain, suggested comparable biological function of abLIM3 as a linker between actin cytoskeleton and cell signaling pathways. AbLIM3 was found to be conserved in vertebrates, as orthologous sequences were characterized for mouse, fish, and frog. In addition, we report the existence of abLIM2 orthologs in fish and frog, suggesting a similar degree of evolutionary conservation. The intracellular localization of the abLIM3 protein was predicted to be nuclear by means of Reinhardt's neural network and the k-nearest neighbor algorithm. The corresponding abLIM3 gene was localized to chromosome 5q32 and spanned 119 kb, organized in 24 exons. An RT-PCR based expression profile available from the human unidentified gene-encoded (HUGE) database demonstrated highest expression for abLIM3 in heart, lung, liver, and brain/cerebellum accompanied by lower expression in multiple other tissues. Furthermore, abLIM3 was expressed in fetal liver, CNS, and spinal cord.

STRING: known and predicted protein-protein associations, integrated and transferred across organisms.

A full description of a protein's function requires knowledge of all partner proteins with which it specifically associates. From a functional perspective, 'association' can mean direct physical binding, but can also mean indirect interaction such as participation in the same metabolic pathway or cellular process. Currently, information about protein association is scattered over a wide variety of resources and model organisms. STRING aims to simplify access to this information by providing a comprehensive, yet quality-controlled collection of protein-protein associations for a large number of organisms. The associations are derived from high-throughput experimental data, from the mining of databases and literature, and from predictions based on genomic context analysis. STRING integrates and ranks these associations by benchmarking them against a common reference set, and presents evidence in a consistent and intuitive web interface. Importantly, the associations are extended beyond the organism in which they were originally described, by automatic transfer to orthologous protein pairs in other organisms, where applicable. STRING currently holds 730,000 proteins in 180 fully sequenced organisms, and is available at http://string.embl.de/.