Inhibition of Metabolic Shift can Decrease Therapy Resistance in Human High-Grade Glioma Cells

抑制代谢转变可降低人类高级别胶质瘤细胞的治疗耐药性

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作者:Gábor Petővári, Titanilla Dankó, Ildikó Krencz, Zoltán Hujber, Hajnalka Rajnai, Enikő Vetlényi, Regina Raffay, Judit Pápay, András Jeney, Anna Sebestyén

Abstract

The high-grade brain malignancy, glioblastoma multiforme (GBM), is one of the most aggressive tumours in central nervous system. The developing resistance against recent therapies and the recurrence rate of GBMs are extremely high. In spite several new ongoing trials, GBM therapies could not significantly increase the survival rate of the patients as significantly. The presence of inter- and intra-tumoral heterogeneity of GBMs arise the problem to find both the pre-existing potential resistant clones and the cellular processes which promote the adaptation mechanisms such as multidrug resistance, stem cell-ness or metabolic alterations, etc. In our work, the in situ metabolic heterogeneity of high-grade human glioblastoma cases were analysed by immunohistochemistry using tissue-microarray. The potential importance of the detected metabolic heterogeneity was tested in three glioma cell lines (grade III-IV) using protein expression analyses (Western blot and WES Simple) and therapeutic drug (temozolomide), metabolic inhibitor treatments (including glutaminase inhibitor) to compare the effects of rapamycin (RAPA) and glutaminase inhibitor combinations in vitro (Alamar Blue and SRB tests). The importance of individual differences and metabolic alterations were observed in mono-therapeutic failures, especially the enhanced Rictor expressions after different mono-treatments in correlation to lower sensitivity (temozolomide, doxycycline, etomoxir, BPTES). RAPA combinations with other metabolic inhibitors were the best strategies except for RAPA+glutaminase inhibitor. These observations underline the importance of multi-targeting metabolic pathways. Finally, our data suggest that the detected metabolic heterogeneity (the high mTORC2 complex activity, enhanced expression of Rictor, p-Akt, p-S6, CPT1A, and LDHA enzymes in glioma cases) and the microenvironmental or treatment induced metabolic shift can be potential targets in combination therapy. Therefore, it should be considered to map tissue heterogeneity and alterations with several cellular metabolism markers in biopsy materials after applying recently available or new treatments.

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