Functional profiling: from microarrays via cell-based assays to novel tumor relevant modulators of the cell cycle

Differential Gene Expression Landscape of Co-Existing Cervical Pre-Cancer Lesions Using RNA-seq

Genetic changes occurring in different stages of pre-cancer lesions reflect causal events initiating and promoting the progression to cancer. Co-existing pre-cancerous lesions including low- and high-grade squamous intraepithelial lesion (LGSIL and HGSIL), and adjacent “normal” cervical epithelium from six formalin-fixed paraffin-embedded samples were selected. Tissues from these 18 samples were isolated using laser-capture microdissection, RNA was extracted and sequenced. RNA-sequencing generated 2.4 billion raw reads in 18 samples, of which ~50.1% mapped to known and annotated genes in the human genome. There were 40 genes up-regulated and 3 down-regulated (normal to LGSIL) in at least one-third of the sample pairs (same direction and FDR p < 0.05) including S100A7 and KLK6. Previous studies have shown that S110A7 and KLK7 are up-regulated in several other cancers, whereas CCL18, CFTR, and SLC6A14, also differentially expressed in two samples, are up-regulated specifically in cervical cancer. These differentially expressed genes in normal to LGSIL progression were enriched in pathways related to epithelial cell differentiation, keratinocyte differentiation, peptidase, and extracellular activities. In progression from LGSIL to HGSIL, two genes were up-regulated and five down-regulated in at least two samples. Further investigations using co-existing samples, which account for all internal confounders, will provide insights to better understand progression of cervical pre-cancer.

Novel roles of Vmp1: inhibition metastasis and proliferation of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most deadly human cancers because of its high incidence of metastasis. Despite extensive efforts, therapies against metastasis of HCC remain underdeveloped. Vacuole membrane protein 1 (Vmp1) was recently identified to be involved in cancer-relevant processes; however, its expression, clinical significance and biological function in HCC progression are still unknown. Therefore, we evaluated the expression of Vmp1 in human HCC specimens. To functionally characterize Vmp1 in HCC, we upregulated its expression in HCCLM3 cells using a plasmid transfection approach, following which both in vitro and in vivo models were used to elucidate its role. A significant downregulation of Vmp1 was found in human HCC tissues and closely correlated with multiple tumor nodes, absence of capsular formation, vein invasion and poor prognosis of HCC. Such expression was verified with HCC cell lines including HepG2, MHCC97-L and HCCLM3, and the Vmp1 expression levels negatively correlated with metastatic potential. Interestingly, upregulation of Vmp1 significantly affects proliferation, migration, invasion and adhesion of HCCLM3 cells. Using a mouse model, we demonstrated that upregulation of Vmp1 was associated with suppression of growth and pulmonary metastases of HCC. Therefore, our data suggest Vmp1 is a novel prognostic marker and potential therapeutic target for metastasis of HCC.

Survivin (BIRC5) cell cycle computational network in human no-tumor hepatitis/cirrhosis and hepatocellular carcinoma transformation

Survivin (BIRC5) relationship with tumor is presented in several papers. However, how the molecular network and interpretation concerning BIRC5 cell cycle between no-tumor hepatitis/cirrhosis and hepatocellular carcinoma (HCC) remains to be elucidated. Here, we constructed and analyzed significant higher expression gene BIRC5 activated and inhibited cell cycle network from HCC versus no-tumor hepatitis/cirrhosis patients (viral infection HCV or HBV) in GEO Dataset by combination of gene regulatory network inference method based on linear programming and decomposition procedure with the CapitalBio MAS 3.0 software based on the integration of public databases including Gene Ontology, KEGG, BioCarta, GenMapp, Intact, UniGene, OMIM, etc. Compared the same and different activated and inhibited BIRC5 network with GO analysis between no-tumor hepatitis/cirrhosis and HCC, our result showed BIRC5 cell cycle network weaker transcription factor activity in both no-tumor hepatitis/cirrhosis and HCC (1); stronger nucleus protein binding but weaker cytoplasm protein binding in no-tumor hepatitis/cirrhosis (2); stronger cytoplasm protein phosphatase binding but weaker ubiquitin-protein ligase activity in HCC (3). Therefore, we inferred BIRC5 cell cycle module less transcription from RNA polymerase II promoter in both no-tumor hepatitis/cirrhosis and HCC (4). We deduced BIRC5 cell cycle module different from more mitosis but less complex-dependent proteasomal ubiquitin-dependent protein catabolism as a result increasing cell division and cell numbers in no-tumor hepatitis/cirrhosis to more protein amino acid autophosphorylation but less negative regulation of ubiquitin ligase activity during mitotic cell cycle as a result increasing growth and cell volume in HCC (5).

Functional genomics and proteomics approaches to study the ERBB network in cancer

Substantial progress in functional genomic and proteomic technologies has opened new perspectives in biomedical research. The sequence of the human genome has been mostly determined and opened new visions on its complexity and regulation. New technologies, like RNAi and protein arrays, allow gathering knowledge beyond single gene analysis. Increasingly, biological processes are studied with systems biological approaches, where qualitative and quantitative data of the components are utilized to model the respective processes, to predict effects of perturbations, and to then refine these models after experimental testing. Here, we describe the potential of applying functional genomics and proteomics, taking the ERBB family of growth-factor receptors as an example to study the signaling network and its impact on cancer.

Automated production of recombinant human proteins as resource for proteome research

Background

An arbitrary set of 96 human proteins was selected and tested to set-up a fully automated protein production strategy, covering all steps from DNA preparation to protein purification and analysis. The target proteins are encoded by functionally uncharacterized open reading frames (ORF) identified by the German cDNA consortium. Fusion proteins were produced in E. coli with four different fusion tags and tested in five different purification strategies depending on the respective fusion tag. The automated strategy relies on standard liquid handling and clone picking equipment.

Results

A robust automated strategy for the production of recombinant human proteins in E. coli was established based on a set of four different protein expression vectors resulting in NusA/His, MBP/His, GST and His-tagged proteins. The yield of soluble fusion protein was correlated with the induction temperature and the respective fusion tag. NusA/His and MBP/His fusion proteins are best expressed at low temperature (25°C), whereas the yield of soluble GST fusion proteins was higher when protein expression was induced at elevated temperature. In contrast, the induction of soluble His-tagged fusion proteins was independent of the temperature. Amylose was not found useful for affinity-purification of MBP/His fusion proteins in a high-throughput setting, and metal chelating chromatography is recommended instead.

Conclusion

Soluble fusion proteins can be produced in E. coli in sufficient qualities and μg/ml culture quantities for downstream applications like microarray-based assays, and studies on protein-protein interactions employing a fully automated protein expression and purification strategy. Future applications might include the optimization of experimental conditions for the large-scale production of soluble recombinant proteins from libraries of open reading frames.

The full-ORF clone resource of the German cDNA Consortium

Background

With the completion of the human genome sequence the functional analysis and characterization of the encoded proteins has become the next urging challenge in the post-genome era. The lack of comprehensive ORFeome resources has thus far hampered systematic applications by protein gain-of-function analysis. Gene and ORF coverage with full-length ORF clones thus needs to be extended. In combination with a unique and versatile cloning system, these will provide the tools for genome-wide systematic functional analyses, to achieve a deeper insight into complex biological processes.

Results

Here we describe the generation of a full-ORF clone resource of human genes applying the Gateway cloning technology (Invitrogen). A pipeline for efficient cloning and sequencing was developed and a sample tracking database was implemented to streamline the clone production process targeting more than 2,200 different ORFs. In addition, a robust cloning strategy was established, permitting the simultaneous generation of two clone variants that contain a particular ORF with as well as without a stop codon by the implementation of only one additional working step into the cloning procedure. Up to 92 % of the targeted ORFs were successfully amplified by PCR and more than 93 % of the amplicons successfully cloned.

Conclusion

The German cDNA Consortium ORFeome resource currently consists of more than 3,800 sequence-verified entry clones representing ORFs, cloned with and without stop codon, for about 1,700 different gene loci. 177 splice variants were cloned representing 121 of these genes. The entry clones have been used to generate over 5,000 different expression constructs, providing the basis for functional profiling applications. As a member of the recently formed international ORFeome collaboration we substantially contribute to generating and providing a whole genome human ORFeome collection in a unique cloning system that is made freely available in the community.

Reduced expression of vacuole membrane protein 1 affects the invasion capacity of tumor cells

Vacuole membrane protein 1 (Vmp1) is described as a cancer-relevant cell cycle modulator, but the function of this protein and its mode of action in tumor progression are still unknown. In this study, we show that the VMP1 mRNA level is significantly reduced in kidney cancer metastases as compared to primary tumors. Further, VMP1 expression is also decreased in the invasive breast cancer cell lines HCC1954 and MDA-MB-231 as compared to the non-invasive cell lines MCF-12A, T-47D and MCF-7. We show for the first time that Vmp1 is a plasma membrane protein and an essential component of initial cell-cell contacts and tight junction formation. It interacts with the tight junction protein Zonula Occludens-1 and colocalizes in spots between neighboring HEK293 cells. Downregulation of VMP1 by RNAi results in loss of cell adherence, and increases the invasion capacity of the non-invasive kidney cancer cell line Caki-2. In conclusion, our findings establish Vmp1 to be a novel cell-cell adhesion protein and that its expression level determines the invasion and metastatic potential of cancer cells.

The potential of high-content high-throughput microscopy in drug discovery

Fluorescence microscopy is a powerful method to study protein function in its natural habitat, the living cell. With the availability of the green fluorescent protein and its spectral variants, almost any gene of interest can be fluorescently labelled in living cells opening the possibility to study protein localization, dynamics and interactions. The emergence of automated cellular systems allows rapid visualization of large groups of cells and phenotypic analysis in a quantitative manner. Here, we discuss recent advances in high-content high-throughput microscopy and its potential application to several steps of the drug discovery process.

High-throughput flow cytometry-based assay to identify apoptosis-inducing proteins

After sequencing the human genome, the challenge ahead is to systematically analyze the functions and disease relation of the proteins encoded. Here the authors describe the application of a flow cytometry-based high-throughput assay to screen for apoptosis-activating proteins in transiently transfected cells. The assay is based on the detection of activated caspase-3 with a specific antibody, in cells overexpressing proteins tagged C- or N-terminally with yellow fluorescent protein. Fluorescence intensities are measured using a flow cytometer integrated with a high-throughput autosampler. The applicability of this screen has been tested in a pilot screen with 200 proteins. The candidate proteins were all verified in an independent microscopy-based nuclear fragmentation assay, finally resulting in the identification of 6 apoptosis inducers.

Retroviral microarray-based platform on nanostructured TiO2 for functional genomics and drug discovery

Living-cell microarrays are powerful tools for functional genomics and drug discovery. However, despite several attempts to improve this technology, it is still a challenge to obtain microarrays of cells efficiently overexpressing or downregulating specific genes to address complex phenotypes. Here, we present a cell-based microarray for phenotype screening on primary and cancer cells based on the localized reverse infection by retroviruses. Viral vectors are immobilized on a nanostructured titanium dioxide (ns-TiO2) film obtained by depositing a supersonic beam of titania clusters on a glass substrate. We validated the retroviral cell array by overexpression of GFP reporter genes in primary and cancer cells, and by RNA interference of p53 in primary cells by analyzing effects in cell growth. We demonstrate that ns-TiO2 retroviral arrays are an enabling tool for the study of gene function of families of genes for complex phenotypes and for the identification of novel drug targets.

Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts

Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.

From genome to proteome: developing expression clone resources for the human genome

cDNA clones have long been valuable reagents for studying the structure and function of proteins. With recent access to the entire human genome sequence, it has become possible and highly productive to compare the sequences of mRNAs to their genes, in order to validate the sequences and protein-coding annotations of each (1,2). Thus, well-characterized collections of human cDNAs are now playing an essential role in defining the structure and function of human genes and proteins. In this review, we will summarize the major collections of human cDNA clones, discuss some limitations common to most of these collections and describe several noteworthy proteomics applications, focusing on the detection and analysis of protein-protein interactions (PPI). These human cDNA collections contain principally two types of cDNA clones. The largest collections comprise cDNAs with full-length protein coding sequences (FL-CDS). Some but not all of these cDNA clones may represent the entire mRNA sequence, but many are missing considerable non-coding UTR sequence, usually at the 5' end. A second type of cDNA clone, a 'full-ORF' (F-ORF) expression clone, is one where the annotated protein-coding sequence, excised of 5' UTR and 3' UTR sequence, has been transferred to a vector designed to facilitate transfer to other vectors for protein expression.

The LIFEdb database in 2006

LIFEdb () integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression (‘Electronic Northern’) of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.