Recently, Setty et al. proposed a lasso regularized regression model that incorporates copy-number variation, DNA methylation levels, TF, and miRNA-mediated regulatory effects to predict differential gene expression in glioblastoma (GBM) [4]. The gene discussed is TF; the disease is glioblastoma.