Abstract
BackgroundTranscription factors are known to play key roles in carcinogenesis and therefore, are gaining popularity as potential therapeutic targets in drug development. A ‘master regulator’ transcription factor often appears to control most of the regulatory activities of the other transcription factors and the associated genes. This ‘master regulator’ transcription factor is at the top of the hierarchy of the transcriptomic regulation. Therefore, it is important to identify and target the master regulator transcription factor for proper understanding of the associated disease process and identifying the best therapeutic option.MethodsWe present a novel two-step computational approach for identification of master regulator transcription factor in a genome. At the first step of our method we test whether there exists any master regulator transcription factor in the system. We evaluate the concordance of two ranked lists of transcription factors using a statistical measure. In case the concordance measure is statistically significant, we conclude that there is a master regulator. At the second step, our method identifies the master regulator transcription factor, if there exists one.ResultsIn the simulation scenario, our method performs reasonably well in validating the existence of a master regulator when the number of subjects in each treatment group is reasonably large. In application to two real datasets, our method ensures the existence of master regulators and identifies biologically meaningful master regulators. An R code for implementing our method in a sample test data can be found in http://www.somnathdatta.org/software.ConclusionWe have developed a screening method of identifying the ‘master regulator’ transcription factor just using only the gene expression data. Understanding the regulatory structure and finding the master regulator help narrowing the search space for identifying biomarkers for complex diseases such as cancer. In addition to identifying the master regulator our method provides an overview of the regulatory structure of the transcription factors which control the global gene expression profiles and consequently the cell functioning.
Highlights
Transcription factors are known to play key roles in carcinogenesis and are gaining popularity as potential therapeutic targets in drug development
We develop a novel two-step statistical approach to test for the existence of a master regulator transcription factor and for subsequent identification of the master regulator, if it exists, from gene expression data alone
As discussed before in the Background section, usually there is a hierarchical structure in the regulation of the transcription factors so that the master regulator controls most of the regulatory activities of the other transcription factors and the associated genes
Summary
Transcription factors are known to play key roles in carcinogenesis and are gaining popularity as potential therapeutic targets in drug development. Majority of the cancer signaling pathways seem to Sikdar and Datta BMC Bioinformatics (2017) 18:79 converge to these sets of transcription factors, and these transcription factors lead to tumor development, progression and cancer metastasis through the controlling of the gene expression patterns [2, 3]. As a result of these features of the transcription factors, in addition to the facts that they are much smaller in number than the oncogenes and have well-regulated expression and activities, transcription factors are gaining popularity as potential therapeutic targets in anti-cancer drug development [3, 4, 7, 8]
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