Conclusion
Collectively, this hypoxia-derived gene signature could become a reliable biomarker for predicting prognosis and therapeutic response and providing theoretical support for hypoxia treatment and precision nursing of GBM patients.
Methods
We retrospectively analyzed the transcriptome profiling and clinicopathological characteristics of GBM from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts. A series of bioinformatic and machine learning methods were comprehensively applied for establishing a hypoxia-derived gene signature in prediction of overall survival, disease-free survival, disease-specific survival, and progression-free survival. The predictive efficacy of this model was assessed with receiver operator characteristic (ROC) and uni- and multivariate cox regression analysis. The associations of this signature with tumor microenvironment and immunotherapeutic response predictors were evaluated across GBM. RT-qPCR and western blotting were presented for validating the expression of ALDH3B1 and CTSZ in human glioma cell lines (U251, SHG-44, and U87) and normal glial cell line HEB.
Objective
Hypoxia presents a salient feature investigated in most solid tumors that holds key roles in cancer progression, including glioblastoma multiforme (GBM). Here, we aimed to construct a hypoxia-derived gene signature for identifying the high-risk GBM patients to guide adjuvant therapy and precision nursing based on signs of hypoxia.
Results
Among hallmarks of cancer, hypoxia acted as a prominent risk factor of GBM prognosis. A hypoxia-derived gene signature displayed efficient ability in predicting clinical outcomes. High risk score indicated undesirable prognosis, recurrence, and progression of GBM. Moreover, this risk score displayed positive correlations to immunity and stromal activation. Combining immunotherapeutic response predictors, high-risk patients more benefited from immunotherapy. ALDH3B1 and CTSZ expression had prominent upregulation in glioma cells than normal glial cells.