Background

Esophageal cancer (ESCA) is one of the deadliest solid malignancies with worse survival rate worldwide. Here, we aimed to establish an immune-gene prognostic signature for predicting patients’ survival and providing accurate targets for personalized therapy or immunotherapy.

Methods

Gene expression profile of patients with ESCA were download from The Cancer Genome Atlas (TCGA) database (dataset 1: n = 159) and immune-related genes from the ImmPORT database. Dataset 1 was subdivided into two groups (dataset 2: n = 80; dataset 3: n = 79). Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature on the three datasets. TIMER and CIBERSORT analysis were used to evaluate the correlation between the prognostic signature and infiltrating immune cells.

Results

We constructed a prognostic signature composed of six immune genes (HSPA6, S100A12, FABP3, DKK1, OSM and NR2F2). Kaplan-Meier curves validated the good predictive ability of the prognostic signature in datasets 1, 2 and 3 (P = 0.0034, P = 0.0081, and P = 0.0363, respectively). The area under the curve (AUC) of the ROC curves validated the predictive accuracy of the immune signature (AUCs = 0.757, 0.800, and 0.701, respectively). We also revealed the good prognostic value of the immune cells, including activated memory CD4 T cells, T follicular helper cells and monocytes. Potential target drugs, including Olopatadine and Amlexanox, were identified for clinical therapies to improve patients’ survival outcomes.

Conclusion

Our study indicated that the immune-related prognostic signature could serve as a novel biomarker for predicting patients’ prognosis and providing new immunotherapy targets in ESCA.

中文翻译：

---

鉴定免疫基因标记和浸润性免疫细胞对食道癌患者的预后价值。

背景

食道癌（ESCA）是最致命的实体恶性肿瘤之一，在世界范围内存活率均较差。在这里，我们旨在建立一种免疫基因预后的特征，以预测患者的生存情况，并为个性化治疗或免疫治疗提供准确的目标。

方法

可从癌症基因组图谱（TCGA）数据库（数据集1：n = 159）下载ESCA患者的基因表达谱，并从ImmPORT数据库下载免疫相关基因。数据集1分为两组（数据集2：n = 80；数据集3：n = 79）。绘制Kaplan-Meier和接收者操作特征（ROC）曲线以验证三个数据集对预后的预​​测作用。TIMER和CIBERSORT分析用于评估预后标志和浸润免疫细胞之间的相关性。

结果

我们构建了由六个免疫基因（HSPA6，S100A12，FABP3，DKK1，OSM和NR2F2）组成的预后标记。Kaplan-Meier曲线验证在数据集1，2和3中的预后签名的良好的预测能力（P  = 0.0034，P  = 0.0081，和P  = 0.0363，分别地）。ROC曲线的曲线下面积（AUC）验证了免疫特征的预测准确性（AUC分别为0.757、0.800和0.701）。我们还揭示了免疫细胞的良好预后价值，包括活化的记忆CD4 T细胞，T卵泡辅助细胞和单核细胞。确定了潜在的靶标药物，包括奥洛他定和Amlexanox，用于临床治疗，以改善患者的生存结果。

结论

我们的研究表明，免疫相关的预后标记可以作为预测患者预后并为ESCA提供新的免疫治疗靶标的新型生物标志物。