基于氧化磷酸化相关基因的三阴性乳腺癌预后模型构建与验证

Construction and validation of an oxidative phosphorylation-related gene prognostic model in triple-negative breast cancer

摘要:

背景与目的 三阴性乳腺癌（TNBC）具有高度侵袭性和较差预后，代谢重编程尤其是氧化磷酸化异常在其进展中发挥重要作用。本研究基于多组学数据，筛选TNBC氧化磷酸化相关风险基因，并构建预后预测模型。方法 基于Human Protein Atlas（HPA）数据库筛选与乳腺癌不良预后相关的基因，结合GSE176078单细胞测序数据及COSMIC细胞系数据，筛选TNBC代谢相关的核心基因。采用TCGA-BRCA Basal-like队列构建预后模型，通过单因素Cox、LASSO及多因素Cox回归筛选独立预后因子，并建立风险评分模型及列线图模型。利用ICGC-BRCA-US队列进行外部验证。进一步采用ESTIMATE及CIBERSORT算法分析风险评分与肿瘤免疫微环境的相关性。结果 共筛选获得63个与乳腺癌不良预后相关的代谢基因，其功能主要富集于氧化磷酸化及ATP能量代谢通路。其中16个基因在TNBC肿瘤细胞中明显高表达，并主要参与电子呼吸传递链过程。最终筛选获得脱氧胞苷三磷酸焦磷酸酶1（dCTP pyrophosphatase 1，DCTPP1）、细胞色素C1（cytochrome C1，CYC1）两个独立预后风险基因，并构建风险评分模型：高风险组患者总体生存期明显低于低风险组（P=0.006）。训练队列中，模型预测1、3、5、10年总生存期的AUC分别为0.664、0.655、0.662和0.775，一致性指数为0.634。联合年龄及M分期建立的列线图模型一致性指数提高至0.726。ICGC队列验证结果显示模型仍具有较稳定的预测能力。免疫浸润分析显示，风险评分与Immune score、Stromal score及ESTIMATE score均呈负相关，而与肿瘤纯度呈正相关；高风险组CD8⁺ T细胞浸润显著降低。结论 本研究基于多组学数据成功构建并验证了TNBC氧化磷酸化相关预后模型。DCTPP1和CYC1可能是影响TNBC不良预后的关键代谢基因，并有望成为治疗靶点。该模型可为TNBC风险分层及个体化治疗提供参考依据。

Abstract:

Background and Aims Triple-negative breast cancer (TNBC) is characterized by strong invasiveness and poor prognosis. Metabolic reprogramming, particularly oxidative phosphorylation (OXPHOS) dysregulation, plays a critical role in TNBC progression. This study aimed to identify OXPHOS-related prognostic genes and construct a prognostic prediction model for TNBC based on multi-omics data.Methods Genes associated with poor prognosis in breast cancer were screened from the Human Protein Atlas database. Combined with GSE176078 single-cell RNA sequencing data and COSMIC cell line data, TNBC-related metabolic genes were identified. A prognostic model was established using the TCGA-BRCA Basal-like cohort through univariate Cox, LASSO, and multivariate Cox regression analyses. A nomogram integrating clinicopathological variables was subsequently constructed. External validation was performed using the ICGC-BRCA-US cohort. In addition, the ESTIMATE and CIBERSORT algorithms were applied to investigate the relationship between the risk score and the tumor immune microenvironment.Results A total of 63 metabolism-related genes associated with poor prognosis in breast cancer were identified, mainly enriched in oxidative phosphorylation and ATP metabolic pathways. Among them, 16 genes were significantly overexpressed in TNBC tumor cells and were primarily involved in the electron transport chain process. The dCTP pyrophosphatase 1 (DCTPP1) and cytochrome C1 (CYC1) were ultimately identified as independent prognostic risk genes and used to construct the risk model. Patients in the high-risk group exhibited significantly worse overall survival than those in the low-risk group (P=0.006). The AUC values for predicting 1-, 3-, 5-, and 10-year overall survival were 0.664, 0.655, 0.662, and 0.775, respectively, with a C-index of 0.634. The nomogram incorporating age and M stage achieved a C-index of 0.726. External validation using the ICGC cohort confirmed the robustness of the model. Immune infiltration analysis demonstrated that the risk score was negatively correlated with Immune score, Stromal score, and ESTIMATE score, but positively correlated with tumor purity. Moreover, CD8⁺ T-cell infiltration was significantly reduced in the high-risk group.Conclusion This study successfully developed and validated an OXPHOS-related prognostic model for TNBC using multi-omics data. DCTPP1 and CYC1 may serve as key metabolic drivers of poor prognosis and therapeutic targets in TNBC. This model may provide a useful tool for prognostic stratification and individualized treatment of TNBC patients.