Despite the existence of many clinical and molecular factors reported that contribute to survival in glioblastoma, prevailing studies fell into partial or local feature selection for survival analysis. We proposed a feature selection strategy including not only joint covariate detection but also its evaluations, and performed it on miRNA expression profiles with glioblastoma. MiR-10b and miR-222 were selected as the most significant two-dimensional feature. Crucially, we integrated in vitro experiments on GBM cells and in vivo studies on a mouse model of human glioma to elucidate the synergistic effects between miR-10b and miR-222. Inhibition of miR-10b and miR-222 strongly suppress GBM cells growth, invasion, and induce apoptosis by co-targeting PTEN and leading to activation of p53 ultimately. We also demonstrated that miR-10b and miR-222 co-target BIM to induce apoptosis independent of p53 status. The results define mir-10b and mir-222 important roles in gliomagenesis and provided a reliable survival analysis strategy.