Dataset Information

In silico identification of transcriptional regulators associated with c-Myc.

ABSTRACT: The development of powerful experimental strategies for functional genomics and accompanying computational tools has brought major advances in the delineation of transcriptional networks in organisms ranging from yeast to human. Regulation of transcription of eukaryotic genes is to a large extent combinatorial. Here, we used an in silico approach to identify transcription factors (TFs) that form recurring regulatory modules with c-Myc, a protein encoded by an oncogene that is frequently disregulated in human malignancies. A recent study identified, on a genomic scale, human genes whose promoters are bound by c-Myc and its heterodimer partner Max in Burkitt's lymphoma cells. Using computational methods, we identified nine TFs whose binding-site signatures are highly overrepresented in this promoter set of c-Myc targets, pointing to possible functional links between these TFs and c-Myc. Binding sites of most of these TFs are also enriched on the set of mouse homolog promoters, suggesting functional conservation. Among the enriched TFs, there are several regulators known to control cell cycle progression. Another TF in this set, EGR-1, is rapidly activated by numerous stress challenges and plays a central role in angiogenesis. Experimental investigation confirmed that c-Myc and EGR-1 bind together on several target promoters. The approach applied here is general and demonstrates how computational analysis of functional genomics experiments can identify novel modules in complex networks of transcriptional regulation.

SUBMITTER: Elkon R

PROVIDER: S-EPMC521640 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature

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In silico identification of transcriptional regulators associated with c-Myc.

Elkon Ran R Zeller Karen I KI Linhart Chaim C Dang Chi V CV Shamir Ron R Shiloh Yosef Y

Nucleic acids research 20040923 17

The development of powerful experimental strategies for functional genomics and accompanying computational tools has brought major advances in the delineation of transcriptional networks in organisms ranging from yeast to human. Regulation of transcription of eukaryotic genes is to a large extent combinatorial. Here, we used an in silico approach to identify transcription factors (TFs) that form recurring regulatory modules with c-Myc, a protein encoded by an oncogene that is frequently disregul ...[more]

PMID: 15388797

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Project description:Lung cancer is the leading cause of cancer-related death and lung adenocarcinoma is its most common subtype. Although genetic alterations have been identified as drivers in subsets of lung adenocarcinoma, they do not fully explain tumor development. Epigenetic alterations have been implicated in the pathogenesis of tumors. To identify epigenetic alterations driving lung adenocarcinoma, we used an improved version of the Tracing Enhancer Networks using Epigenetic Traits method (TENET 2.0) in primary normal lung and lung adenocarcinoma cells. We found over 32,000 enhancers that appear differentially activated between normal lung and lung adenocarcinoma. Among the identified transcriptional regulators inactivated in lung adenocarcinoma vs. normal lung, NKX2-1 was linked to a large number of silenced enhancers. Among the activated transcriptional regulators identified, CENPA, FOXM1, and MYBL2 were linked to numerous cancer-specific enhancers. High expression of CENPA, FOXM1, and MYBL2 is particularly observed in a subgroup of lung adenocarcinomas and is associated with poor patient survival. Notably, CENPA, FOXM1, and MYBL2 are also key regulators of cancer-specific enhancers in breast adenocarcinoma of the basal subtype, but they are associated with distinct sets of activated enhancers. We identified individual lung adenocarcinoma enhancers linked to CENPA, FOXM1, or MYBL2 that were associated with poor patient survival. Knockdown experiments of FOXM1 and MYBL2 suggest that these factors regulate genes involved in controlling cell cycle progression and cell division. For example, we found that expression of TK1, a potential target gene of a MYBL2-linked enhancer, is associated with poor patient survival. Identification and characterization of key transcriptional regulators and associated enhancers in lung adenocarcinoma provides important insights into the deregulation of lung adenocarcinoma epigenomes, highlighting novel potential targets for clinical intervention.

Dataset Information

In silico identification of transcriptional regulators associated with c-Myc.

Publications

In silico identification of transcriptional regulators associated with c-Myc.

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