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.

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.

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.