Song Ze-Bing, Yu Yang, Zhang Guo-Pei, Li Shao-Qiang
Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Front Cell Dev Biol. 2021 Oct 5;9:728574. doi: 10.3389/fcell.2021.728574. eCollection 2021.
Hepatocellular carcinoma (HCC) is one of the major cancer-related deaths worldwide. Genomic instability is correlated with the prognosis of cancers. A biomarker associated with genomic instability might be effective to predict the prognosis of HCC. In the present study, data of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used. A total of 370 HCC patients from the TCGA database were randomly classified into a training set and a test set. A prognostic signature of the training set based on nine overall survival (OS)-related genomic instability-derived genes (SLCO2A1, RPS6KA2, EPHB6, SLC2A5, PDZD4, CST2, MARVELD1, MAGEA6, and SEMA6A) was constructed, which was validated in the test and TCGA and ICGC sets. This prognostic signature showed more accurate prediction for prognosis of HCC compared with tumor grade, pathological stage, and four published signatures. Cox multivariate analysis revealed that the risk score could be an independent prognostic factor of HCC. A nomogram that combines pathological stage and risk score performed well compared with an ideal model. Ultimately, paired differential expression profiles of genes in the prognostic signature were validated at mRNA and protein level using HCC and paratumor tissues obtained from our institute. Taken together, we constructed and validated a genomic instability-derived gene prognostic signature, which can help to predict the OS of HCC and help us to explore the potential therapeutic targets of HCC.
肝细胞癌(HCC)是全球主要的癌症相关死亡原因之一。基因组不稳定性与癌症预后相关。一种与基因组不稳定性相关的生物标志物可能对预测HCC的预后有效。在本研究中,使用了来自癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)数据库的HCC患者数据。来自TCGA数据库的370例HCC患者被随机分为训练集和测试集。基于9个与总生存期(OS)相关的基因组不稳定性衍生基因(SLCO2A1、RPS6KA2、EPHB6、SLC2A5、PDZD4、CST2、MARVELD1、MAGEA6和SEMA6A)构建了训练集的预后特征,并在测试集以及TCGA和ICGC数据集中进行了验证。与肿瘤分级、病理分期和四个已发表的特征相比,该预后特征对HCC预后的预测更准确。Cox多因素分析显示,风险评分可能是HCC的独立预后因素。与理想模型相比,结合病理分期和风险评分的列线图表现良好。最终,使用从我们研究所获得的HCC和癌旁组织,在mRNA和蛋白质水平验证了预后特征中基因的配对差异表达谱。综上所述,我们构建并验证了一种基因组不稳定性衍生基因预后特征,其有助于预测HCC的OS,并有助于我们探索HCC潜在的治疗靶点。