To further elucidate how the tumor metabolic status is regulated by transcription factors (TFs), we adopted tumor-context-specific TF regulatory networks, which is based on ARACNe algorithm and proposed by Giorgi et al. [18], to infer the significantly enriched master TFs that potentially drive the conversion of tumor metabolic phenotypes (HGLO and LGHO) from one to the other using MARINa in each cancer type (Additional file 13: Data 5). The gene discussed is TF; the disease is cancer.