Ma Jie, Liu Dan, Li Yang, Tang Lei, Gao Xukun, Zhu Feng
Department of Thoracic Surgery, Anhui Chest Hospital, Clinical College of Chest, Anhui Medical University, Hefei, China.
Cell Biochem Biophys. 2025 Jun 12. doi: 10.1007/s12013-025-01802-6.
Esophageal cancer (EC) is a highly aggressive malignancy, with esophageal squamous cell carcinoma (ESCC) accounting for the majority of cases worldwide. Despite advances in treatment, the prognosis for ESCC remains poor, underscoring the urgent need for reliable prognostic biomarkers to guide clinical decision-making. In this study, we constructed a novel prognostic model by integrating cuproptosis-related genes with ferroptosis and immune-associated genes-three critical pathways implicated in tumor progression and immune modulation. Gene expression and clinical data from ESCC patients were obtained from the GSE53625 and TCGA-ESCC cohorts. Ferroptosis- and immune-related genes (FIRGs) were sourced from FerrDb and ImmPort databases, and their association with cuproptosis-related genes was determined via Pearson correlation, yielding a set of cuproptosis-associated FIRGs (FI-CRGs). Thirteen prognostically relevant FI-CRGs were identified through Cox regression analysis and used to develop a risk score model (FI-CRS). The FI-CRS demonstrated robust predictive performance in both the training cohort (GSE53625, n = 179) and the independent validation cohort (TCGA-ESCC, n = 81), where high-risk patients exhibited significantly reduced overall survival (p < 0.05). Functional enrichment analyses (GO and KEGG) revealed strong associations between high FI-CRS and immunoregulatory pathways. Further investigation showed notable differences in immune cell infiltration and drug sensitivity between risk groups. Additionally, a prognostic nomogram incorporating clinical features (age, gender, TNM staging, and FI-CRS) was established to enhance individualized survival prediction. Altogether, this study presents a novel, integrative in silico framework that not only offers promising biomarkers for prognosis but also provides mechanistic insights into ESCC biology, potentially informing future therapeutic strategies.
食管癌（EC）是一种侵袭性很强的恶性肿瘤，其中食管鳞状细胞癌（ESCC）在全球大多数病例中占主导。尽管治疗取得了进展，但ESCC的预后仍然很差，这凸显了迫切需要可靠的预后生物标志物来指导临床决策。在本研究中，我们通过整合铜死亡相关基因与铁死亡和免疫相关基因构建了一种新型预后模型，这三条关键途径与肿瘤进展和免疫调节有关。ESCC患者的基因表达和临床数据来自GSE53625和TCGA-ESCC队列。铁死亡和免疫相关基因（FIRGs）来自FerrDb和ImmPort数据库，并通过Pearson相关性确定它们与铜死亡相关基因的关联，从而产生一组与铜死亡相关的FIRGs（FI-CRGs）。通过Cox回归分析确定了13个与预后相关的FI-CRGs，并用于建立风险评分模型（FI-CRS）。FI-CRS在训练队列（GSE53625，n = 179）和独立验证队列（TCGA-ESCC，n = 81）中均表现出强大的预测性能，其中高危患者的总生存期显著降低（p < 0.05）。功能富集分析（GO和KEGG）显示高FI-CRS与免疫调节途径之间存在强关联。进一步研究表明，风险组之间在免疫细胞浸润和药物敏感性方面存在显著差异。此外，还建立了一个包含临床特征（年龄、性别、TNM分期和FI-CRS）的预后列线图，以加强个性化生存预测。总之，本研究提出了一种新颖的、整合的计算机框架，不仅为预后提供了有前景的生物标志物，还为ESCC生物学提供了机制性见解，可能为未来的治疗策略提供参考。
