摘要

    越来越多的证据表明，自噬在乳腺癌（BC）的进展中起着至关重要的作用。因此，本研究的目的是研究自噬相关基因（ARG）的预后价值，并开发一种基于ARG的模型来评估BC患者的5年总生存期（OS）。我们从癌症基因组图谱（TCGA）数据库中的一个大型BC队列（N = 1007）中获得了ARG表达谱。 LASSO和Cox回归分析证实了ARGs与OS之间的相关性。基于独立的预后变量建立了预测模型。因此，进行了与时间有关的接收机工作曲线（ROC），校准图，决策曲线和子组分析，以确定基于ARG的模型的预测性能。使用LASSO和多元Cox回归分析确定了四个ARG（ATG4A，IFNG，NRG1和SERPINA1）。基于四个ARG和两个临床病理风险因素（年龄和TNM分期）构建了一个基于ARG的模型，将患者分为高风险和低风险组。低风险组患者的5年OS高于高风险组（P <0.0001）。 5年时的时间依赖性ROC表明，在训练队列（AUC：0.731 vs 0.640，P <0.01）和验证队列（AUC：0.804 vs 0.671，P <0.01）中，四种基于ARG的工具的预后准确性均优于TNM分期。 ）。四个ARG（ATG4A，IFNG，NRG1和SERPINA1）的突变频率分别为0.9％，2.8％，8％和1.3％。我们建立并验证了一种新颖的基于ARG的四个诺模图，这是一种预测BC五年OS的可靠方法，可以帮助肿瘤学家确定有效的治疗策略。

    Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy-related genes (ARGs) and develop a ARG-based model to evaluate 5-year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time-dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG-based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG-based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high-risk and low-risk groups. The 5-year OS of patients in the low-risk group was higher than that in the high-risk group (P < 0.0001). Time-dependent ROC at 5 years indicated that the four ARG–based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG–based nomogram, a credible approach to predict 5-year OS in BC, which can assist oncologists in determining effective therapeutic strategies.

    https://onlinelibrary.wiley.com/doi/full/10.1111/jcmm.15551