Arsenic Trioxide and (−)-Gossypol Synergistically Target Glioma Stem-Like Cells via Inhibition of Hedgehog and Notch Signaling

Abstract

Glioblastoma is one of the deadliest malignancies and is virtually incurable. Accumulating evidence indicates that a small population of cells with a stem-like phenotype is the major culprit of tumor recurrence. Enhanced DNA repair capacity and expression of stemness marker genes are the main characteristics of these cells. Elimination of this population might delay or prevent tumor recurrence following radiochemotherapy. The aim of this study was to analyze whether interference with the Hedgehog signaling (Hh) pathway or combined Hh/Notch blockade using small-molecule inhibitors can efficiently target these cancer stem cells and sensitize them to therapy. Using tumor sphere lines and primary patient-derived glioma cultures we demonstrate that the Hh pathway inhibitor GANT61 (GANT) and the arsenic trioxide (ATO)-mediated Hh/Notch inhibition are capable to synergistically induce cell death in combination with the natural anticancer agent (−)-Gossypol (Gos). Only ATO in combination with Gos also strongly decreased stemness marker expression and prevented sphere formation and recovery. These synergistic effects were associated with distinct proteomic changes indicating diminished DNA repair and markedly reduced stemness. Finally, using an organotypic brain slice transplantation model, we show that combined ATO/Gos treatment elicits strong growth inhibition or even complete elimination of tumors. Collectively, our data show for the first time that ATO and Gos, two drugs that can be used in the clinic, represent a promising targeted therapy approach for the synergistic elimination of glioma stem-like cells.

Autophagy in Cancer Cell Death

“…Arsenic trioxide was shown to induce ACD and cell death in various tumor cell populations in multiple studies, including our own [14,[56][57][58]. Considering that arsenic trioxide is already clinically used to treat acute promyelocytic leukemia (APL) [59] and easily crosses the blood-brain-barrier [60], this drug could be particularly interesting for hard-to-treat cancers, such as brain tumors (primary or metastases).…”

“…Interestingly, we could also recently show that the combination of arsenic trioxide and AT-101 caused a strong upregulation of HMOX1 in glioma stem-like cells (GSCs) [56], indicating that more specialized cell populations can also be targeted with drugs employing these pathways. In summary, we recently provided novel evidence that the decrease in mitochondrial mass and function induced by AT-101 is due to robust over activation of mitophagy that finally culminates in the demise of the cancer cells.…”

Autophagy as a Potential Therapy for Malignant Glioma

“…On the other hand, As 2 O 3 decreased the population of stem cell-like cancer cells (CSLC) in U87-MG, U251-MG, and U373MG glioma cell lines by blocking the Notch signaling pathway, decreasing the concentration of Nocht1 and Hes1 [251]. In addition, Linder et al reported that a combination of As 2 O 3 plus AT101 (a BH3-mimetics, inhibitor of the pro-apoptotic proteins Bcl-2, Bcl-xL, and Mcl-1) showed a synergistic effect against CSLC by inhibiting the Hedgehog and Notch signaling pathways [252]. In a neurosphere model of glioblastoma, a decrease in growth and proliferation was observed, as well as an increase in caspase-3 levels after treating with As 2 O 3 the HSR-GBM1, 040622 (TMZ-resistant) and 040821 (TMZ-sensitive) cell lines.…”

“…• Increases caspase 3, inhibits PTCH1b, N-Myc, and GLI2 (transcriptional targets of Hg pathway), and inhibits HES5 and HEY1 (transcriptional targets of Notch pathway) [252].…”

Glioblastoma: State of the Art and Future Perspectives

“…The original articles in this special issue present novel findings on molecular mechanisms of radiosensitization, radioresistance and acquired resistance to therapy (Kessler et al, Müller-Längle et al, Shah et al, Llaguno-Munive et al) [1,2,3,4], cell migration (Nowicki et al, Hübner et al) [5,6], intracellular drug levels (Colin et al) [7], strategies targeting renewal capacities of cancer stem-like cells (Gravina et al, Sansalone et al, Linder et al) [8,9,10], mathematic modeling of synergy, machine learning, deep learning (Kim et al, Hana et al, Wong et al) [11,12,13], distinct signaling pathways (Barbagallo et al, Akgül et al, Bensalma et al, Saito et al, Liu et al) [14,15,16,17,18], prognostic and predictive effects of imaging patterns (Jungk et al, Puig et al) [19,20], tumor-associated epilepsy (Berendsen et al) [21], and novel models and experimental therapeutic approaches (Berthier et al, Offenhäuser et al, Privat-Maldonado et al, Lozada-Delgado et al) [22,23,24,25].…”