Novel prognostic features and personalized treatment strategies for mitochondria-related genes in glioma patients.

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, Identify a mitochondrial gene with immune-related features that could be used to predict the prognosis of glioma patients.

METHODS

Gliomas data 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(Least absolute shrinkage and selection operator) regression was applied to identify prognostic features, and area and nomograms under the ROC(Receiver Operating Characteristic) curve were used to assess the robustness of the model. Single sample genomic enrichment analysis (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

COX assembly mitochondrial protein homolog (), Cytochrome c oxidase protein 20 homolog () and Cytochrome b-c1 complex subunit 7 () were identified as prognostic key genes in glioma, with , progressively increasing and progressively decreasing with decreasing risk scores. ROC curve analysis of the TCGA training set model yielded AUC (Area Under The Curve) values >0.8 for 1-, 2- and 3-year survival, and the model was associated with both CD8+ T cells and immune checkpoints. Finally, using cellMiner database and molecular docking, it was confirmed that binds covalently to Amonafide 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 Survival in glioma patients, and we also provide glioma chemotherapeutic agents that may be mitochondria-related targets.