Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor type that is typically metastatic upon diagnosis. We have a poor understanding of the factors that control SCLC progression and metastasis. TheNFIB transcription factor is frequently amplified in mouse models of SCLC, but clear evidence that NFIB promotes SCLC in vivo is lacking. We report that in mouse models, Nfib amplifications are far more frequent in liver metastases over primary SCLC, suggesting roles in tumor progression/metastasis. Overexpression of Nfib in a sensitized mouse model led to acceleration of SCLC, indicating that Nfib functions as a bona fide oncogene. Suppression of Nfib expression in cell lines derived from the doxycycline-inducible Rb/p53/TET-Nfib model led to increased apoptosis and suppression of proliferation. Transcriptional analysis revealed that Nfib regulates the expression of genes related to axon guidance, focal adhesion and extracellular matrix-receptor interactions. These data indicate that Nfib is a potent oncogene in SCLC, and the enrichment of Nfib amplifications in liver metastases over primary SCLC points to Nfib as a candidate driver of SCLC metastasis.
Pubmed ID: 27613844 RIS Download
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Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
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View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
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