Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Nutrition and Food Hygiene, Chongqing Medical University, Chongqing, China.
BMC Genomics. 2023 Jul 10;24(1):385. doi: 10.1186/s12864-023-09496-x.
Identifying reliable biomarkers could effectively predict esophagus carcinoma (EC) patients with poor prognosis. In this work, we constructed an immune-related gene pairs (IRGP) signature to evaluate the prognosis of EC.
The IRGP signature was trained by the TCGA cohort and validated by three GEO datasets, respectively. Cox regression model together with LASSO was applied to construct the overall survival (OS) associated IRGP. 21 IRGPs consisting of 38 immune-related genes were included in our signature, according to which patients were stratified into high- and low-risk groups. The results of Kaplan-Meier survival analyses indicated that high-risk EC patients had worse OS than low-risk group in the training set, meta-validation set and all independent validation datasets. After adjustment in multivariate Cox analyses, our signature continued to be an independent prognostic factor of EC and the signature-based nomogram could effectively predict the prognosis of EC sufferers. Besides, Gene Ontology analysis revealed this signature is related to immunity. 'CIBERSORT' analysis revealed the infiltration levels of plasma cells and activated CD4 memory T cells in two risk groups were significantly different. Ultimately, we validated the expression levels of six selected genes from IRGP index in KYSE-150 and KYSE-450.
This IRGP signature could be applied to select EC patients with high mortality risk, thereby improving prospects for the treatment of EC.
识别可靠的生物标志物可以有效地预测食管癌（EC）预后不良的患者。在这项工作中，我们构建了一个免疫相关基因对（IRGP）特征来评估 EC 的预后。
IRGP 特征由 TCGA 队列进行训练，并分别由三个 GEO 数据集进行验证。Cox 回归模型和 LASSO 一起被用来构建与总体生存（OS）相关的 IRGP。根据该模型，我们的特征包含 21 个由 38 个免疫相关基因组成的基因对，根据这些基因对患者被分为高风险和低风险组。Kaplan-Meier 生存分析的结果表明，在训练集、meta 验证集和所有独立验证数据集中，高风险 EC 患者的 OS 明显差于低风险组。在多变量 Cox 分析调整后，我们的特征仍然是 EC 的独立预后因素，基于该特征的列线图可以有效地预测 EC 患者的预后。此外，GO 分析表明该特征与免疫有关。'CIBERSORT'分析显示，两个风险组的浆细胞和活化的 CD4 记忆 T 细胞的浸润水平有显著差异。最后，我们验证了 IRGP 指数中 6 个选定基因在 KYSE-150 和 KYSE-450 中的表达水平。
这个 IRGP 特征可以用来选择具有高死亡率风险的 EC 患者，从而改善 EC 的治疗前景。
