Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Department of Chinese Traditional Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Oncol Res. 2023 Nov 15;32(1):199-212. doi: 10.32604/or.2023.030969. eCollection 2023.
Oxidative stress (OS) is intimately associated with tumorigenesis and has been considered a potential therapeutic strategy. However, the OS-associated therapeutic target for esophageal squamous cell carcinoma (ESCC) remains unconfirmed. In our study, gene expression data of ESCC and clinical information from public databases were downloaded. Through LASSO-Cox regression analysis, a risk score (RS) signature map of prognosis was constructed and performed external verification with the GSE53625 cohort. The ESTIMATE, xCell, CIBERSORT, TIMER, and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment (IM). Afterward, functional enrichment analysis clarified the underlying mechanism of the model. Nomogram was utilized for forecasting the survival rate of individual ESCC cases. As a result, we successfully constructed an OS-related genes (OSRGs) model and found that the survival rate of high-risk groups was lower than that of low-risk groups. The AUC of the ROC verified the strong prediction performance of the signal in these two cohorts further. According to independent prognostic analysis, the RS was identified as an independent risk factor for ESCC. The nomogram and follow-up data revealed that the RS possesses favorable predictive value for the prognosis of ESCC patients. qRT-PCR detection demonstrated increased expression of MPC1, COX6C, CYB5R3, CASP7, and CYCS in esophageal cancer patients. In conclusion, we have constructed an OSRGs model for ESCC to predict patients' prognosis, offering a novel insight into the potential application of the OSRGs model in ESCC.
氧化应激（OS）与肿瘤发生密切相关，已被认为是一种潜在的治疗策略。然而，食管鳞状细胞癌（ESCC）的 OS 相关治疗靶点仍未得到证实。在我们的研究中，从公共数据库下载了 ESCC 的基因表达数据和临床信息。通过 LASSO-Cox 回归分析，构建了预后风险评分（RS）特征图谱，并通过 GSE53625 队列进行了外部验证。采用 ESTIMATE、xCell、CIBERSORT、TIMER 和 ImmuCellAI 算法分析浸润免疫细胞并生成免疫微环境（IM）。然后，进行功能富集分析以阐明模型的潜在机制。使用列线图预测个体 ESCC 病例的生存率。结果，我们成功构建了一个与 OS 相关的基因（OSRGs）模型，并发现高危组的生存率低于低危组。ROC 的 AUC 进一步验证了该信号在这两个队列中的强大预测性能。根据独立预后分析，RS 被确定为 ESCC 的独立危险因素。列线图和随访数据表明，RS 对 ESCC 患者的预后具有良好的预测价值。qRT-PCR 检测显示食管癌患者中 MPC1、COX6C、CYB5R3、CASP7 和 CYCS 的表达增加。总之，我们构建了一个用于预测 ESCC 患者预后的 OSRGs 模型，为 OSRGs 模型在 ESCC 中的潜在应用提供了新的视角。
