Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, China; Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, China.
Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, China; Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, China.
Int Immunopharmacol. 2020 Oct;87:106795. doi: 10.1016/j.intimp.2020.106795. Epub 2020 Jul 21.
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.
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.
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.
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.
食管癌（ESCA）是全球致死率最高的恶性实体肿瘤之一。本研究旨在建立一种免疫基因预后signature，以预测患者的生存情况，并为个体化治疗或免疫治疗提供准确靶点。
从癌症基因组图谱（TCGA）数据库（数据集 1：n=159）中下载 ESCA 患者的基因表达谱，并从 ImmPORT 数据库中下载免疫相关基因。数据集 1 进一步分为两组（数据集 2：n=80；数据集 3：n=79）。绘制 Kaplan-Meier 曲线和受试者工作特征（ROC）曲线，以验证预后 signature 对三个数据集的预测效果。使用 TIMER 和 CIBERSORT 分析评估预后 signature 与浸润免疫细胞的相关性。
构建了一个由 6 个免疫基因（HSPA6、S100A12、FABP3、DKK1、OSM 和 NR2F2）组成的预后 signature。Kaplan-Meier 曲线验证了该预后 signature 在数据集 1、2 和 3 中的良好预测能力（P=0.0034，P=0.0081 和 P=0.0363）。ROC 曲线的曲线下面积（AUC）验证了免疫 signature 的预测准确性（AUCs=0.757、0.800 和 0.701）。我们还揭示了包括激活的记忆 CD4 T 细胞、滤泡辅助 T 细胞和单核细胞在内的免疫细胞的良好预后价值。确定了包括 Olopatadine 和 Amlexanox 在内的潜在靶向药物，用于改善患者的生存结局。
本研究表明，免疫相关的预后 signature 可以作为预测患者预后的新型生物标志物，并为 ESCA 提供新的免疫治疗靶点。
