Development of a prognostic model for hepatocellular carcinoma using genes involved in aerobic respiration.
Development of a prognostic model for hepatocellular carcinoma using genes involved in aerobic respiration.
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利用参与有氧呼吸的基因开发肝细胞癌的预后模型
DOI：
10.18632/aging.203021
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发表时间：
2021-04-26
期刊：
影响因子：
--
通讯作者：
Ma Y
中科院分区：
文献类型：
--
作者：
Rao J;Wu X;Zhou X;Deng R;Ma Y
肝细胞癌（HCC）是全球癌症相关死亡的第二大原因。目前，最近的风险分层仅关注肝功能和肿瘤特征。因此，本研究的目的是开发一个预测模型的基础上参与有氧呼吸的基因。分析来自TCGA和ICGC群组的匹配的肿瘤和正常组织以鉴定15个重叠的差异表达基因。对TCGA队列中15个基因的考克斯单变量分析显示，它们都与HCC患者的疾病特异性生存（DSS）相关。使用LASSO估计和惩罚系数λ的最佳值，选择12个基因用于预后模型，然后将TCGA队列中的HCC患者二分为低风险组和高风险组。单因素和多因素考克斯分析显示低危组患者生存率较高。ICGC队列风险评分模型的验证结果与TCGA队列一致。总之，本研究通过对有氧呼吸相关基因的综合分析，建立并验证了肝癌的预后模型。该模型可能有助于为HCC患者开发个性化治疗。
Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. Currently, recent risk stratification has only focused on liver function and tumor characteristics. Thus, the purpose of this study was to develop a prognostic model based on genes involved in aerobic respiration. Matched tumor and normal tissues from TCGA and ICGC cohorts were analyzed to identify 15 overlapping differential expressed genes. Cox univariate analysis of the 15 genes in the TCGA cohort revealed they were all associated with disease-specific survival (DSS) in HCC patients. Using LASSO estimation and the optimal value for penalization coefficient lambda 12 genes were selected for the prognostic model, and then HCC patients in the TCGA cohort were dichotomized into low-risk and high-risk groups. Univariate and multivariate Cox analysis demonstrated patients in low-risk group had better survival. Validation of the risk score model with the ICGC cohort produces results consistent with those of the TCGA cohort. In conclusion, this study developed and validated a prognostic model of HCC through a comprehensive analysis of genes involved in aerobic respiration. This model may help develop personalized treatments for patients with HCC.
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