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.

中文翻译：

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基于MIPRIP 2.0基因调控网络方法，对19种不同癌症类型的TERT调控进行建模。

背景技术端粒酶逆转录酶基因TERT的重新激活是大多数癌症无限增殖的主要特征。但是，仅部分理解了基本的监管流程。结果我们从服务器来源收集了调控因子结合信息，以构建一个通用的人类和小鼠基因调控网络。推进我们的“基于混合整数线性规划的调节相互作用预测因子”（MIPRIP）方法，我们确定了跨19种不同人类癌症的TERT最常见的癌症类型特异性调节剂。通过使用ETS1转录因子对TERT启动子突变的黑色素瘤子集中的众所周知的TERT调节，验证了结果。我们改进的MIPRIP2 R-package和相关的通用监管网络可从https://www.microsoft.com/en-us/en/免费下载。//github.com/KoenigLabNM/MIPRIP。结论MIPRIP 2.0鉴定了TERT的常见以及肿瘤类型特异性调节剂。该软件可轻松应用于转录组数据集，以预测所研究的任何基因和疾病/状况的基因调控。