Xiao Jian, Wang Gang, Zhu Chuming, Liu Kanghui, Wang Yuanhang, Shen Kuan, Fan Hao, Ma Xiang, Xu Zekuan, Yang Li
Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China.
Department of General Surgery, Liyang People's Hospital, Liyang Branch Hospital of Jiangsu Province Hospital, Liyang, Jiangsu Province, China.
Heliyon. 2023 Jun 5;9(6):e17017. doi: 10.1016/j.heliyon.2023.e17017. eCollection 2023 Jun.
Recently, several studies have indicated the great potential of gene expression signature of the primary tumor in predicting lymph node metastasis; however, few current gene biomarkers can predict lymph node status and prognosis in gastric cancer (GC). Thus, we used the RNA-seq data from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes between pathological lymph node-negative (pN0) and positive (pN+) patients and to establish a gene signature that could predict lymph node metastasis. Meanwhile, the robustness of identified gene signatures was validated in an independent dataset Asian Cancer Research Group (n = 300). In this study, our thirty-three gene-based signature was highly correlated with lymph node metastasis and could successfully discriminate pN + patients in the training set (Area under the receiver operating characteristic curve = 0.951). Moreover, Disease-free survival ( = 0.0029) and overall survival ( = 0.026) were significantly worse in high-risk compared with low-risk patients overall and when confined to pN0 patients only ( < 0.0001). Of note, this gene signature also proved useful in predicting lymph node status and survival in the validation cohort. The present study suggests a thirty-three gene-based signature that could effectively predict lymph node metastasis and prognosis in GC.
最近，多项研究表明原发性肿瘤的基因表达特征在预测淋巴结转移方面具有巨大潜力；然而，目前很少有基因生物标志物能够预测胃癌（GC）的淋巴结状态和预后。因此，我们使用来自癌症基因组图谱（TCGA）的RNA测序数据，以识别病理淋巴结阴性（pN0）和阳性（pN+）患者之间的差异表达基因，并建立一个能够预测淋巴结转移的基因特征。同时，在一个独立数据集亚洲癌症研究组（n = 300）中验证了所识别基因特征的稳健性。在本研究中，我们基于33个基因的特征与淋巴结转移高度相关，并且能够在训练集中成功区分pN+患者（受试者操作特征曲线下面积 = 0.951）。此外，总体而言，高危患者与低危患者相比，无病生存期（P = 0.0029）和总生存期（P = 0.026）显著更差，仅局限于pN0患者时也是如此（P < 0.0001）。值得注意的是，该基因特征在验证队列中也被证明可用于预测淋巴结状态和生存期。本研究提出了一种基于33个基因的特征，其能够有效预测GC中的淋巴结转移和预后。
