Heme Oxygenase-1 Predicts Risk Stratification and Immunotherapy Efficacy in Lower Grade Gliomas

Background: Gliomas are the most common tumors in human brains with unpleasing outcomes. Heme oxygenase-1 (HMOX1, HO-1) was a potential target for human cancers. However, their relationship remains incompletely discussed. Methods: We employed a total of 952 lower grade glioma (LGG) patients from TCGA and CGGA databases, and twenty-nine samples in our hospital for subsequent analyses. Expression, mutational, survival, and immune profiles of HMOX1 were comprehensively evaluated. The risk signature was constructed by LASSO Cox regression analysis. And a nomogram model was generated to predict survival of LGG patients. Single-cell transcriptomic sequencing data were also employed to investigated the role of HMOX1 in cancer cells. Results: We found that HMOX1 was overexpressed and was related to poorer survival in gliomas. HMOX1-related genes (HRGs) were involved in several immune-oncological pathways. Patients in the high-risk group had significantly shorter overall survival time. The risk score was positively correlated with the abundance of resting memory CD4+ T cells, M1, M2 macrophages, and activated dendritic cells. Additionally, immunotherapy showed potent efficacy in low-risk group. And patients with lower HMOX1 expression were predicted to have better response to immunotherapies, suggesting that immunotherapies combined with HMOX1 inhibition may execute good responses. Moreover, significant correlations were found between HMOX1 expression and single-cell functional states including angiogenesis, hypoxia, and metastasis. Finally, a nomogram including clinicopathologic features and the established risk signature could predict 1-, 3- and 5-year survival in LGG patients. Conclusion: HMOX1 impacts immune infiltration and correlates with poorer outcome in patients with primary lower grade glioma. Importantly, HMOX1 were related to oncological functional states including angiogenesis, hypoxia, and metastasis. A risk signature and subsequent nomogram are established based on HRGs to robustly predict patient overall survival, with a potential for clinical utilization.