Bai Shuheng, Chen Ling, Yan Yanli, Wang Xuan, Jiang Aimin, Li Rong, Kang Haojing, Feng Zhaode, Li Guangzu, Ma Wen, Zhang Jiangzhou, Ren Juan
Department of Radiotherapy, Oncology Department, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Department of Chemotherapy, Oncology Department, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Front Cell Dev Biol. 2022 Feb 8;9:796156. doi: 10.3389/fcell.2021.796156. eCollection 2021.
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. 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. 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. 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.
肾透明细胞癌(KIRC)是一种恶性疾病,对公众健康构成严重威胁。追踪肿瘤进展信息并建立相关的动态预后模型对于KIRC来说是必要的。由于免疫相互作用以及缺氧对KIRC患者预后的影响,识别缺氧免疫相关基因并构建预后模型至关重要。利用t-SNE和ImmuCellAI对基因表达数据进行分析,以确定KIRC患者的缺氧和免疫状态。采用COX和Lasso回归来识别一些缺氧免疫相关的特征基因,并进一步基于这些基因构建预后风险模型。同时进行内部和外部验证以构建预后模型。最后,通过CMap数据集筛选出一些潜在有效的药物。我们发现高缺氧和低免疫状态往往会导致较差的总生存期(OS)。包括PLAUR、UCN、PABPC1L、SLC16A12、NFE2L3和KCNAB1在内的六个基因被识别并纳入我们的缺氧免疫相关预后风险模型。内部验证显示,构建的模型在1年、3年、4年和5年OS的曲线下面积(AUC)分别为0.768、0.754、0.775和0.792。外部验证中,1年、3年、4年和5年OS的AUC分别为0.768、0.739、0.763和0.643。此外,决策曲线分析结果显示出良好的临床有效性。最后,我们发现四种药物(包括伏立诺他、氟羟皮质酮、恶喹酸和氟他胺)可能在缓解或逆转严重缺氧和免疫细胞浸润不良的状态方面有效且高效。我们构建的基于缺氧免疫相关基因的预后模型具有良好的有效性和临床应用价值。此外,还筛选出了一些小分子药物来缓解严重缺氧和免疫细胞浸润不良的情况。