Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach

Background Reactivation of the telomerase reverse transcriptase gene TERT is a central feature for unlimited proliferation of the majority of cancers. However, the underlying regulatory processes are only partly understood. Results We assembled regulator binding information from serveral sources to construct a generic human and mouse gene regulatory network. Advancing our “Mixed Integer linear Programming based Regulatory Interaction Predictor” (MIPRIP) approach, we identified the most common and cancer-type specific regulators of TERT across 19 different human cancers. The results were validated by using the well-known TERT regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the TERT promoter. Our improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at https://github.com/KoenigLabNM/MIPRIP . Conclusion MIPRIP 2.0 identified common as well as tumor type specific regulators of TERT . The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease/condition under investigation.