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Systems analysis identifies melanoma-enriched pro-oncogenic networks controlled by the RNA binding protein CELF1.

ABSTRACT: Melanomas are well-known for their altered mRNA expression profiles. Yet, the specific contribution of mRNA binding proteins (mRBPs) to melanoma development remains unclear. Here we identify a cluster of melanoma-enriched genes under the control of CUGBP Elav-like family member 1 (CELF1). CELF1 was discovered with a distinct prognostic value in melanoma after mining the genomic landscape of the 692 known mRBPs across different cancer types. Genome-wide transcriptomic, proteomic, and RNA-immunoprecipitation studies, together with loss-of-function analyses in cell lines, and histopathological evaluation in clinical biopsies, revealed an intricate repertoire of CELF1-RNA interactors with minimal overlap with other malignancies. This systems approach uncovered the oncogene DEK as an unexpected target and downstream effector of CELF1. Importantly, CELF1 and DEK were found to represent early-induced melanoma genes and adverse indicators of overall patient survival. These results underscore novel roles of CELF1 in melanoma, illustrating tumor type-restricted functions of RBPs in cancer.

SUBMITTER: Cifdaloz M

PROVIDER: S-EPMC5740069 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Systems analysis identifies melanoma-enriched pro-oncogenic networks controlled by the RNA binding protein CELF1.

Cifdaloz Metehan M Osterloh Lisa L Graña Osvaldo O Riveiro-Falkenbach Erica E Ximénez-Embún Pilar P Muñoz Javier J Tejedo Cristina C Calvo Tonantzin G TG Karras Panagiotis P Olmeda David D Miñana Belén B Gómez-López Gonzalo G Cañon Estela E Eyras Eduardo E Guo Haihong H Kappes Ferdinand F Ortiz-Romero Pablo L PL Rodríguez-Peralto Jose L JL Megías Diego D Valcárcel Juan J Soengas María S MS

Nature communications 20171221 1

Melanomas are well-known for their altered mRNA expression profiles. Yet, the specific contribution of mRNA binding proteins (mRBPs) to melanoma development remains unclear. Here we identify a cluster of melanoma-enriched genes under the control of CUGBP Elav-like family member 1 (CELF1). CELF1 was discovered with a distinct prognostic value in melanoma after mining the genomic landscape of the 692 known mRBPs across different cancer types. Genome-wide transcriptomic, proteomic, and RNA-immunopr ...[more]

PMID: 29269732

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Project description:BackgroundIn many cancers, microRNAs (miRs) contribute to metastatic progression by modulating phenotypic reprogramming processes such as epithelial-mesenchymal plasticity. This can be driven by miRs targeting multiple mRNA transcripts, inducing regulated changes across large sets of genes. The miR-target databases TargetScan and DIANA-microT predict putative relationships by examining sequence complementarity between miRs and mRNAs. However, it remains a challenge to identify which miR-mRNA interactions are active at endogenous expression levels, and of biological consequence.MethodsWe developed a workflow to integrate TargetScan and DIANA-microT predictions into the analysis of data-driven associations calculated from transcript abundance (RNASeq) data, specifically the mutual information and Pearson's correlation metrics. We use this workflow to identify putative relationships of miR-mediated mRNA repression with strong support from both lines of evidence. Applying this approach systematically to a large, published collection of unique melanoma cell lines - the Ludwig Melbourne melanoma (LM-MEL) cell line panel - we identified putative miR-mRNA interactions that may contribute to invasiveness. This guided the selection of interactions of interest for further in vitro validation studies.ResultsSeveral miR-mRNA regulatory relationships supported by TargetScan and DIANA-microT demonstrated differential activity across cell lines of varying matrigel invasiveness. Strong negative statistical associations for these putative regulatory relationships were consistent with target mRNA inhibition by the miR, and suggest that differential activity of such miR-mRNA relationships contribute to differences in melanoma invasiveness. Many of these relationships were reflected across the skin cutaneous melanoma TCGA dataset, indicating that these observations also show graded activity across clinical samples. Several of these miRs are implicated in cancer progression (miR-211, -340, -125b, -221, and -29b). The specific role for miR-29b-3p in melanoma has not been well studied. We experimentally validated the predicted miR-29b-3p regulation of LAMC1 and PPIC and LASP1, and show that dysregulation of miR-29b-3p or these mRNA targets can influence cellular invasiveness in vitro.ConclusionsThis analytic strategy provides a comprehensive, systems-level approach to identify miR-mRNA regulation in high-throughput cancer data, identifies novel putative interactions with functional phenotypic relevance, and can be used to direct experimental resources for subsequent experimental validation. Computational scripts are available: http://github.com/uomsystemsbiology/LMMEL-miR-miner.

Dataset Information

Systems analysis identifies melanoma-enriched pro-oncogenic networks controlled by the RNA binding protein CELF1.

Publications

Systems analysis identifies melanoma-enriched pro-oncogenic networks controlled by the RNA binding protein CELF1.

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