Novel prognostic features and personalized treatment strategies for mitochondria-related genes in glioma patients - Wu, Ji; Zhou, Jiabin; Chai, Yibo; Qin, Chengjian; Cai, Yuankun; Xu, Dongyuan; Lei, Yu; Mei, Zhimin; Li, Muhua; Shen, Lei; Fang, Guoxing; Yang, Zhaojian; et al. (Frontiers in Endocrinology, 2023)
Background: Gliomas are the most common intracranial nervous system tumours that are highly malignant and aggressive, and mitochondria are an important marker of metabolic reprogramming of tumour cells, the prognosis of which cannot be accurately predicted by current histopathology. Therefore, we sought to identify a mitochondrial gene with immune-related features that could be used to predict the prognosis of glioma patients. Methods: Genomic and clinical data for gliomas were downloaded from the TCGA database and mitochondrial-associated genes were obtained from the MITOCARTA 3.0 dataset. The CGGA, kamoun and gravendeel databases were used as external datasets. LASSO regression was applied to identify prognostic features, and area and nomograms under the ROC curve were used to assess the robustness of the model. ssGSEA was employed to explore the relationship between model genes and immune infiltration, and drug sensitivity was used to identify targeting drugs. Cellular studies were then performed to demonstrate drug killing against tumours. Results:Three mitochondria-related genes (CMC1, COX20 and UQCRB) were identified as prognostic key genes in glioma, with UQCRB, CMC1 progressively increasing and COX20 progressively decreasing with decreasing risk scores. ROC curve analysis of the TCGA training set model yielded AUC values >0.8 for 1-, 2- and 3-year survival, a new nomogram was constructed to predict patient OS, and the model was associated with both CD8+ T cells and immune checkpoints. And the protein levels of COX20, CMC1 and UQCRB were highly expressed in glioma tissues. Finally, using cellMiner database and molecular docking, it was confirmed that UQCRB binds covalently to Amonafide via lysine at position 78 and threonine at position 82, while cellular assays showed that Amonafide inhibits glioma migration and invasion. Conclusion: Our three mitochondrial genomic composition-related features accurately predict OS in glioma patients, and we also provide glioma chemotherapeutic agents that may be mitochondria-related targets.