Abstract
Background The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC. Methods The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis. Results 8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK. Conclusion The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.
Highlights
Ovarian cancer (OC) is characterized by relatively high incidence, high mortality rate, and poor prognosis [1, 2]
Heat map results showed that 6 hypoxic genes, including A-kinase anchoring protein 12 (AKAP12), ALDOC, angiopoietin-like 4 (ANGPTL4), CITED2, PPP1R15A, and transforming growth factor beta-induced protein (TGFBI), were highly expressed in the high hypoxia risk group, which indicated that patients in the group tended to develop hypoxic microenvironments
Our results suggested that the above 8 hypoxiaassociated gene risk model could be used as an independent prognostic factor for OC patients, which may represent a convenient detection in clinic
Summary
Ovarian cancer (OC) is characterized by relatively high incidence, high mortality rate, and poor prognosis [1, 2]. Tumor cells adapt by generating energy in oxygen-independent ways by inducing the expression of genes involved in tumor progression [10]. Hypoxia can increase the resistance to radiotherapy and chemotherapy and lead to the decline of cell immunity [11,12,13]. Hypoxic environment is significantly related to the poor prognosis in patients with OC [14]. Cancer immunotherapy can target the cells of the immune system [15]. A detailed understanding of the interactions between cancer, hypoxia, and the immune system may be vital for the recognition of potential new immunotherapeutic strategies and targets for OC patients. International Journal of Endocrinology data to develop a hypoxia risk model to predict the immune microenvironment in OC patients
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