Fei Hongjun, Chen Xiongming
Department of Reproductive Genetics, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Specialty, Shanghai Jiao Tong University School of Medicine Shanghai 200030, China.
Am J Cancer Res. 2022 May 15;12(5):2337-2349. eCollection 2022.
The interaction between the immune cells and the host immune system with the tumor cells is significantly associated with the initiation and progression of prostate adenocarcinoma (PRAD), whereas the application of immune-related genes (IRGs) for the prognosis evaluation of PRAD patients is still lacking. In this study, we aimed to identify IRGs with prognostic values and to develop a clinically effective risk model. Wilcoxon rank-sum test and univariate Cox analysis were applied to identify the differentially expressed immune-related genes (DEIRGs) related to the survival of PRAD patients. The Least absolute shrinkage and selection operator (LASSO) analysis was performed to identify the independent prognostic DEIRGs and to establish an immune risk score prognostic model. The reliability and veracity of the prognostic model were validated in PRAD patients from the internal cohort (The Cancer Genome Atlas, TCGA dataset) and the external cohort (International Cancer Genome Consortium, ICGC dataset), respectively. Six of the 193 identified DEIRGs were survival-associated in PRAD patients. Five prognostic DEIRGs ( and ) were selected to construct the immune-related prognostic model with optimal robustness. In the 2 independent cohorts we chose, PRAD patients could be effectively stratified according to our risk model. Patients with high risk scores had worse survival. Clinical correlation analysis proved that the risk score was associated with advanced clinicopathologic features. Multivariate analysis indicated that the risk model was an independent prognostic indicator. We also established a nomogram based on the risk score model for clinical application. Additionally, the risk score model was correlated with immune cell infiltration and reflected the status of the immune microenvironment. The prognostic value of the five immune-related genes used in the prognostic model was also validated. Our immune-related prognostic model was an effective tool that could not only serve as a predictor for prognosis, but also provide potential prognostic and therapeutic molecular biomarkers for optimizing personalized therapies in clinical practice.
免疫细胞与宿主免疫系统和肿瘤细胞之间的相互作用与前列腺腺癌（PRAD）的发生和进展显著相关，而免疫相关基因（IRGs）在PRAD患者预后评估中的应用仍较为缺乏。在本研究中，我们旨在识别具有预后价值的IRGs并建立一个临床有效的风险模型。应用Wilcoxon秩和检验和单因素Cox分析来识别与PRAD患者生存相关的差异表达免疫相关基因（DEIRGs）。进行最小绝对收缩和选择算子（LASSO）分析以识别独立的预后DEIRGs并建立免疫风险评分预后模型。分别在内部队列（癌症基因组图谱，TCGA数据集）和外部队列（国际癌症基因组联盟，ICGC数据集）的PRAD患者中验证了预后模型的可靠性和准确性。在193个鉴定出的DEIRGs中，有6个与PRAD患者的生存相关。选择5个预后DEIRGs（和）来构建具有最佳稳健性的免疫相关预后模型。在我们选择的2个独立队列中，PRAD患者可以根据我们的风险模型进行有效分层。高风险评分的患者生存情况较差。临床相关性分析证明风险评分与晚期临床病理特征相关。多因素分析表明风险模型是一个独立的预后指标。我们还基于风险评分模型建立了一个列线图用于临床应用。此外，风险评分模型与免疫细胞浸润相关并反映了免疫微环境的状态。用于预后模型的5个免疫相关基因的预后价值也得到了验证。我们的免疫相关预后模型是一个有效的工具，不仅可以作为预后的预测指标，还可以为优化临床实践中的个性化治疗提供潜在的预后和治疗分子生物标志物。
