Background

In the view that immune-related genes play a crucial role in breast cancer progression and long-term patient outcomes, we aimed to identify a novel gene signature based on immune-related genes to improve the prognostic prediction of breast cancer.

Methods

RNA sequencing data and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate and multivariate Cox regression analyses were conducted to establish the immune-related prognostic signature (IRPS). Then, the IRPS was validated by Kaplan–Meier analyses, time-dependent ROC curve analyses and multivariate Cox regression analyses. External validation was conducted in GSE96058. Nomogram combining IRPS with clinical factors was developed and then validated by time-dependent ROC curve analyses and calibration plots. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the expression level of immune-related genes in tumor and normal tissues.

Results

The IRPS based on 4 immune-related genes (CCL1, VGF, TSLP, FABP9) were constructed. Patients in the low-risk group had significantly better overall survival than those in the high-risk group (p = 0.0011 in the training set, p = 0.0043 in the validation set, p < 0.0001 in the entire set, p < 0.001 in the external validation set). Multivariate analyses indicated that IRPS could independently predict OS in the training set (HR, 0.48; 95% CI, 0.24–0.83; p = 0.009), validation set (HR, 0.55; 95% CI, 0.34–0.90; p = 0.018), entire set (HR, 0.52; 95% CI, 0.36–0.75; p < 0.001) and external validation set (HR: 0.74, 95% CI: 0.59–0.92, p = 0.007). Sequentially, we establish a nomogram by integrating IRPS and clinical factors, which showed satisfactory predictive performance with 3-year, 5-year, 10-year AUC of 0.701, 0.706 and 0.694. Results of qRT-PCR validated that higher expression level of FABP9, CCL1 and VGF and lower expression level of TSLP in tumor samples compared to normal tissues.

Conclusions

Collectively, a four-gene based IRPS was developed and validated for patients with breast cancer. As an independent and robust predictor, the IRPS was constructive to risk stratification of breast cancer.

中文翻译：

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鉴定与乳腺癌肿瘤微环境相关的新型免疫相关预后特征

背景

鉴于免疫相关基因在乳腺癌进展和长期患者预后中起着至关重要的作用，我们旨在确定基于免疫相关基因的新基因特征，以改善乳腺癌的预后预测。

方法

RNA测序数据和临床信息来自癌症基因组图谱（TCGA）。进行单变量和多变量 Cox 回归分析以确定免疫相关预后特征 (IRPS)。然后，通过 Kaplan-Meier 分析、时间依赖性 ROC 曲线分析和多变量 Cox 回归分析验证 IRPS。外部验证在 GSE96058 中进行。开发了将 IRPS 与临床因素相结合的列线图，然后通过时间相关的 ROC 曲线分析和校准图进行验证。进行定量实时聚合酶链反应（qRT-PCR）以验证肿瘤和正常组织中免疫相关基因的表达水平。

结果

构建了基于4个免疫相关基因（CCL1、VGF、TSLP、FABP9）的IRPS。低风险组患者的总生存期明显优于高风险组患者（训练集 p = 0.0011，验证集 p = 0.0043，整个集 p < 0.0001，p < 0.001 在外部验证集）。多变量分析表明，IRPS 可以独立预测训练集（HR，0.48；95% CI，0.24-0.83；p = 0.009）、验证集（HR，0.55；95% CI，0.34-0.90；p = 0.018）中的 OS , 整组 (HR, 0.52; 95% CI, 0.36–0.75; p < 0.001) 和外部验证集 (HR: 0.74, 95% CI: 0.59–0.92, p = 0.007)。随后，我们通过整合 IRPS 和临床因素建立列线图，显示出令人满意的预测性能，3 年、5 年、10 年 AUC 分别为 0.701、0.706 和 0.694。

结论

总体而言，针对乳腺癌患者开发并验证了一种基于四基因的 IRPS。作为一个独立且稳健的预测指标，IRPS 对乳腺癌的风险分层具有建设性。