Identification of Hypoxia-Immune-Related Gene Signatures and Construction of a Prognostic Model in Kidney Renal Clear Cell Carcinoma

被引:6
|
作者
Bai, Shuheng [1 ]
Chen, Ling [2 ]
Yan, Yanli [1 ]
Wang, Xuan [1 ]
Jiang, Aimin [2 ]
Li, Rong [1 ]
Kang, Haojing [1 ]
Feng, Zhaode [1 ]
Li, Guangzu [1 ]
Ma, Wen [3 ]
Zhang, Jiangzhou [3 ]
Ren, Juan [1 ]
机构
[1] Xi An Jiao Tong Univ, Affiliated Hosp 1, Oncol Dept, Dept Radiotherapy, Xian, Peoples R China
[2] Xi An Jiao Tong Univ, Affiliated Hosp 1, Oncol Dept, Dept Chemotherapy, Xian, Peoples R China
[3] Xian Jiaotong Univ Xian, Med Sch, Xian, Peoples R China
关键词
hypoxia; kidney clear cell carcinoma; prognosis; immune infiltrate cells; bioinformatic analysis; ENDOTHELIAL GROWTH-FACTOR; TRANSCRIPTION FACTORS; INDUCIBLE FACTORS; CANCER; PROLIFERATION; IMMUNOTHERAPY; PROGRESSION; METASTASIS; FLUTAMIDE; MIGRATION;
D O I
10.3389/fcell.2021.796156
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Introduction: Kidney renal clear cell carcinoma (KIRC), a kind of malignant disease, is a severe threat to public health. Tracking the information of tumor progression and conducting a related dynamic prognosis model are necessary for KIRC. It is crucial to identify hypoxia-immune-related genes and construct a prognostic model due to immune interaction and the influence of hypoxia in the prognosis of patients with KIRC.Methods: The hypoxia and immune status of KIRC patients were identified by utilizing t-SNE and ImmuCellAI for gene expression data. COX and Lasso regression were used to identify some hypoxia-immune-related signature genes and further construct a prognostic risk model based on these genes. Internal and external validations were also conducted to construct a prognostic model. Finally, some potentially effective drugs were screened by the CMap dataset.Results: We found that high-hypoxia and low-immune status tend to induce poor overall survival (OS). Six genes, including PLAUR, UCN, PABPC1L, SLC16A12, NFE2L3, and KCNAB1, were identified and involved in our hypoxia-immune-related prognostic risk model. Internal verification showed that the area under the curve (AUC) for the constructed models for 1-, 3-, 4-, and 5-year OS were 0.768, 0.754, 0.775, and 0.792, respectively. For the external verification, the AUC for 1-, 3-, 4-, and 5-year OS were 0.768, 0.739, 0.763, and 0.643 respectively. Furthermore, the decision curve analysis findings demonstrated excellent clinical effectiveness. Finally, we found that four drugs (including vorinostat, fludroxycortide, oxolinic acid, and flutamide) might be effective and efficient in alleviating or reversing the status of severe hypoxia and poor infiltration of immune cells.Conclusion: Our constructed prognostic model, based on hypoxia-immune-related genes, has excellent effectiveness and clinical application value. Moreover, some small-molecule drugs are screened to alleviate severe hypoxia and poor infiltration of immune cells.
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页数:17
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