Ni Jing, Wang Mengyun, Wang Tianpei, Yan Caiwang, Ren Chuanli, Li Gang, Ding Yanbing, Li Huizhang, Du Lingbin, Jiang Yue, Chen Jiaping, Wang Yanong, Xu Dazhi, Zhu Meng, Dai Juncheng, Ma Hongxia, Hu Zhibin, Shen Hongbing, Wei Qingyi, Jin Guangfu
Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, China.
Fundam Res. 2022 Nov 9;4(5):1331-1338. doi: 10.1016/j.fmre.2022.09.031. eCollection 2024 Sep.
To investigate whether genetic variants may provide additional prognostic value to improve the existing clinical staging system for gastric cancer (GC), we performed two genome-wide association studies (GWASs) of GC survival in the Jiangsu ( = 1049) and Shanghai ( = 1405) cohorts. By using a TCGA dataset, we validated genetic markers identified from a meta-analysis of these two Chinese cohorts to determine GC survival-associated loci. Then, we constructed a weighted polygenic hazard score (PHS) and developed a nomogram in combination with clinical variables. We also evaluated prognostic accuracy with the time-dependent receiver operating characteristic (ROC) curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). We identified a single nucleotide polymorphism (SNP) of rs1618332 at 15q15.1 that was associated with the survival of GC patients with a value of 4.12 × 10, and we also found additional 25 SNPs having consistent associations among these two Chinese cohort and TCGA cohort. The PHS derived from these 26 SNPs (PHS-26) was an independent prognostic factor for GC survival (all < 0.001). The 5-year AUC of PHS-26 was 0.68, 0.66 and 0.67 for Jiangsu, Shanghai and their pooled cohorts, respectively, which increased to 0.80, 0.82 and 0.81, correspondingly, after being integrated into a nomogram together with variables of the clinical model. The PHS-26 could improve the NRIs by 16.20%, 4.90% and 8.70%, respectively, and the IDIs by 11.90%, 8.00% and 9.70%, respectively. The 26-SNP based PHS could substantially improve the accuracy of prognostic assessment and might facilitate precision medicine for GC patients.
为了研究基因变异是否可为改善现有的胃癌（GC）临床分期系统提供额外的预后价值，我们在江苏（n = 1049）和上海（n = 1405）队列中开展了两项关于GC生存的全基因组关联研究（GWAS）。通过使用TCGA数据集，我们验证了从这两个中国队列的荟萃分析中鉴定出的基因标记，以确定与GC生存相关的基因座。然后，我们构建了加权多基因风险评分（PHS），并结合临床变量开发了列线图。我们还使用时间依赖性受试者工作特征（ROC）曲线、净重新分类改善（NRI）和综合鉴别改善（IDI）评估了预后准确性。我们在15q15.1处鉴定出一个与GC患者生存相关的单核苷酸多态性（SNP）rs1618332，其P值为4.12×10⁻⁵，并且我们还在这两个中国队列和TCGA队列中发现了另外25个具有一致关联的SNP。源自这26个SNP的PHS（PHS - 26）是GC生存的独立预后因素（所有P < 0.001）。PHS - 26在江苏、上海及其合并队列中的5年AUC分别为0.68、0.66和0.67，在与临床模型变量一起整合到列线图后，相应地增加到0.80、0.82和0.81。PHS - 26可分别将NRI提高16.20%、4.90%和8.70%，将IDI分别提高11.90%、8.00%和9.70%。基于26个SNP的PHS可显著提高预后评估的准确性，并可能有助于GC患者的精准医疗。
