Nol12 is a multifunctional RNA binding protein at the nexus of RNA and DNA metabolism.

To counteract the breakdown of genome integrity, eukaryotic cells have developed a network of surveillance pathways to prevent and resolve DNA damage. Recent data has recognized the importance of RNA binding proteins (RBPs) in DNA damage repair (DDR) pathways. Here, we describe Nol12 as a multifunctional RBP with roles in RNA metabolism and genome maintenance. Nol12 is found in different subcellular compartments-nucleoli, where it associates with ribosomal RNA and is required for efficient separation of large and small subunit precursors at site 2; the nucleoplasm, where it co-localizes with the RNA/DNA helicase Dhx9 and paraspeckles; as well as GW/P-bodies in the cytoplasm. Loss of Nol12 results in the inability of cells to recover from DNA stress and a rapid p53-independent ATR-Chk1-mediated apoptotic response. Nol12 co-localizes with DNA repair proteins in vivo including Dhx9, as well as with TOPBP1 at sites of replication stalls, suggesting a role for Nol12 in the resolution of DNA stress and maintenance of genome integrity. Identification of a complex Nol12 interactome, which includes NONO, Dhx9, DNA-PK and Stau1, further supports the protein's diverse functions in RNA metabolism and DNA maintenance, establishing Nol12 as a multifunctional RBP essential for genome integrity.

RSK regulates activated BRAF signalling to mTORC1 and promotes melanoma growth.

The Ras/mitogen-activated protein kinase (MAPK) signalling cascade regulates various biological functions, including cell growth, proliferation and survival. As such, this pathway is often deregulated in cancer, including melanomas, which frequently harbour activating mutations in the NRAS and BRAF oncogenes. Hyperactive MAPK signalling is known to promote protein synthesis, but the mechanisms by which this occurs remain poorly understood. Here, we show that expression of oncogenic forms of Ras and Raf promotes the constitutive activation of the mammalian target of rapamycin (mTOR). Using pharmacological inhibitors and RNA interference, we find that the MAPK-activated protein kinase RSK (p90 ribosomal S6 kinase) is partly required for these effects. Using melanoma cell lines carrying activating BRAF mutations, we show that ERK/RSK signalling regulates assembly of the translation initiation complex and polysome formation, as well as the translation of growth-related messenger RNAs containing a 5'-terminal oligopyrimidine (TOP) motif. Accordingly, we find that RSK inhibition abrogates tumour growth in mice. Our findings indicate that RSK may be a valuable therapeutic target for the treatment of tumours characterized by deregulated MAPK signalling, such as melanoma.

Formation of the eIF4F translation-initiation complex determines sensitivity to anticancer drugs targeting the EGFR and HER2 receptors.

Elucidating how cancer cells respond to antagonists of HER receptor family members is critical to understanding mechanisms of therapeutic resistance that arise in patients. In large part, resistance to such agents appears to arise from deregulation of the phosphatidylinositol-3-kinase (PI3K)/Akt/mTOR pathway. mTOR-dependent phosphorylation of the translation repressor 4E-BP1 leads to its dissociation from eIF4E, thereby causing an increase in the formation of the eIF4F complex, which also comprises eIF4G and eIF4A. In this study, we show that trastuzumab, cetuximab, and erlotinib all decrease the formation of the eIF4F complex in breast, colon, and head and neck cancer cells, respectively. Ectopic expression of eIF4E restores the trastuzumab-dependent defect in eIF4F formation, renders cells resistant to the trastuzumab-mediated decrease in cell proliferation, and rescues breast cancer xenografts from inhibition by trastuzumab. In breast tumor specimens, the level of eIF4E expression is associated with the therapeutic response to a trastuzumab-based regimen. Together, our findings suggest that formation of the eIF4F complex may be a critical determinant of the response to anticancer drugs that target HER2 and epidermal growth factor receptor.

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model.

BACKGROUND: To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. RESULTS: To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. CONCLUSIONS: MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis.

M@IA: a modular open-source application for microarray workflow and integrative datamining.

Microarray technology is a widely used approach to gene expression analysis. Many tools for microarray management and data analysis have been developed, and recently new methods have been proposed for deciphering biological pathways by integrating microarray data with other data sources. However, to improve microarray analysis and provide meaningful gene interaction networks, integrated software solutions are still needed. Therefore, we developed M@IA, an environment for DNA microarray data analysis allowing gene network reconstruction. M@IA is a microarray integrated application which includes all of the steps of a microarray study, from MIAME-compliant raw data storage and processing gene expression analysis. Furthermore, M@IA allows automatic gene annotation based on ontology, metabolic/signalling pathways, protein interaction, miRNA and transcriptional factor associations, as well as integrative analysis of gene interaction networks. Statistical and graphical methods facilitate analysis, yielding new hypotheses on gene expression data. To illustrate our approach, we applied M@IA modules to microarray data taken from an experiment on liver tissue. We integrated differentially expressed genes with additional biological information, thus identifying new molecular interaction networks that are associated with fibrogenesis. M@IA is a new application for microarray management and data analysis, offering functional insights into microarray data by the combination of gene expression data and biological knowledge annotation based on interactive graphs. M@IA is an interactive multi-user interface based on a flexible modular architecture and it is freely available for academic users at http://maia.genouest.org.

Upregulation of the tumor suppressor gene menin in hepatocellular carcinomas and its significance in fibrogenesis.

The molecular mechanisms underlying the progression of cirrhosis toward hepatocellular carcinoma were investigated by a combination of DNA microarray analysis and literature data mining. By using a microarray screening of suppression subtractive hybridization cDNA libraries, we first analyzed genes differentially expressed in tumor and nontumor livers with cirrhosis from 15 patients with hepatocellular carcinomas. Seventy-four genes were similarly recovered in tumor (57.8% of differentially expressed genes) and adjacent nontumor tissues (64% of differentially expressed genes) compared with histologically normal livers. Gene ontology analyses revealed that downregulated genes (n = 35) were mostly associated with hepatic functions. Upregulated genes (n = 39) included both known genes associated with extracellular matrix remodeling, cell communication, metabolism, and post-transcriptional regulation gene (e.g., ZFP36L1), as well as the tumor suppressor gene menin (multiple endocrine neoplasia type 1; MEN1). MEN1 was further identified as an important node of a regulatory network graph that integrated array data with array-independent literature mining. Upregulation of MEN1 in tumor was confirmed in an independent set of samples and associated with tumor size (P = .016). In the underlying liver with cirrhosis, increased steady-state MEN1 mRNA levels were correlated with those of collagen alpha2(I) mRNA (P < .01). In addition, MEN1 expression was associated with hepatic stellate cell activation during fibrogenesis and involved in transforming growth factor beta (TGF-beta)-dependent collagen alpha2(I) regulation. In conclusion, menin is a key regulator of gene networks that are activated in fibrogenesis associated with hepatocellular carcinoma through the modulation of TGF-beta response.

Hepatocyte iron loading capacity is associated with differentiation and repression of motility in the HepaRG cell line.

High liver iron content is a risk factor for developing hepatocellular carcinoma (HCC). However, HCC cells are always iron-poor. Therefore, an association between hepatocyte iron storage capacity and differentiation is suggested. To characterize biological processes involved in iron loading capacity, we used a cDNA microarray to study the differentiation of the human HepaRG cell line, from undifferentiated proliferative cells to hepatocyte differentiated cells. We were able to identify genes modulated along HepaRG differentiation, leading us to propose new genes not previously associated with HCC. Moreover, using Gene Ontology annotations, we demonstrated that HepaRG hepatocyte iron loading capacity occurred both with the repression of genes involved in cell motility, signal transduction, and biosynthesis and with the appearance of genes linked to lipid metabolism and immune response. These results provide new insights in the understanding of the relationship between iron and hepatocyte differentiation during iron-related hepatic diseases.

Upregulation of DNA repair genes in active cirrhosis associated with hepatocellular carcinoma.

Phenotypic changes in injured livers involve complex network of genes whose interplays may lead to fibrosis and cirrhosis, a major risk of hepatocellular carcinoma. Gene expression profiles in fibrotic livers were analyzed by using cDNA microarray, hierarchical clustering and gene ontology. Analyses of a major cluster of upregulated genes in cirrhosis identified a new set of genes involved in DNA repair and damage. The upregulation of DNA repair genes was confirmed by real-time quantitative polymerase chain reaction and associated with necroinflammatory activity (P<0.001). Increased DNA repair activity in cirrhosis with inflammatory activity may reflect increased DNA damages as a consequence of chronic liver injury.

Delineation of a 2.8 megabases region harboring a potential tumor suppressor gene involved in renal cell carcinoma, that is commonly deleted from chromosome 14.

MATERIALS AND METHODS: To investigate the genetic alterations that occur during the development of renal cell carcinomas (RCC), we used 20 microsatellite markers to examine 48 renal cell carcinomas for allelic losses of chromosome arm 14q. RESULTS: We identified 14q LOH in 31% of cases. Twelve tumors were entirely lacking the 14q arm and three were partially deleted. For the first time on fresh tumors, these findings led to the delineation of a 17.9 Mb region between markers D14S281 and D14S277 that is commonly deleted. Interestingly, this segment overlaps with the previously reported 37.8 Mb commonly deleted region. CONCLUSION: Taken together these results allowed us to define a new 2.8 Mb segment between markers D14S588 and D14S277 that potentially harbors a tumor suppressor gene involved in the development of RCC which can be reached by positional cloning.