[1]吴翠婷,周雪辉,张婉馨.基于生物学信息分析筛选晚期肝细胞癌患者接受PD-1 抑制剂治疗后糖酵解相关基因差异表达并构建生存获益模型与验证[J].现代检验医学杂志,2023,38(05):34-39.[doi:10.3969/j.issn.1671-7414.2023.05.007]
　WU Cuiting,ZHOU Xuehui,ZHANG Wanxin.Differential Expression of Glycolysis-related Genes in Patients with Advanced Hepatocellular Carcinoma Treated with PD-1 Inhibitors Screened Based on Biological Information Analysis, and Survival Benefit Model Constructed and Verified[J].Journal of Modern Laboratory Medicine,2023,38(05):34-39.[doi:10.3969/j.issn.1671-7414.2023.05.007]
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基于生物学信息分析筛选晚期肝细胞癌患者接受PD-1 抑制剂治疗后糖酵解相关基因差异表达并构建生存获益模型与验证()
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《现代检验医学杂志》[ISSN:/CN:]

卷:
第38卷
期数:
2023年05期
页码:
34-39
栏目:
论著
出版日期:
2023-09-15

文章信息/Info

Title:
Differential Expression of Glycolysis-related Genes in Patients with Advanced Hepatocellular Carcinoma Treated with PD-1 Inhibitors Screened Based on Biological Information Analysis, and Survival Benefit Model Constructed and Verified
文章编号:
1671-7414（2023）05-034-06
作者:
吴翠婷; 周雪辉; 张婉馨
（南方医科大学珠江医院药剂科 ，广州 510280）
Author(s):
WU Cuiting; ZHOU Xuehui; ZHANG Wanxin
（Department of Pharmacy, Zhujiang Hospital of Southern Medical University, Guangzhou 510280, China）
关键词:
肝细胞癌; 糖酵解相关基因; 程序性细胞死亡蛋白-1 抑制剂
分类号:
R735.7；R730.43
DOI:
10.3969/j.issn.1671-7414.2023.05.007
文献标志码:
A
摘要:
目的 基于糖酵解基因构建风险评分模型，对经程序性细胞死亡蛋白-1（programmed cell death protein 1，PD-1）抑制剂治疗后的晚期肝细胞癌（hepatocellular carcinoma ，HCC）患者的生存获益状况进行预测分析。方法 从癌症基因组图谱 (the cancer genome atlas ，TCGA) 选取369 例接受PD-1 抑制剂治疗的HCC 患者和50 例正常肝组织的临床数据和高通量测序数据，患者年龄53 ～ 72（69.23 ± 6.61）岁；使用“limma” R 包进行差异分析，筛选出肝细胞癌组织中异常表达的糖酵解相关基因，将获得的基因进行多因素COX 回归分析；利用LASSO 分析筛选关键预测因子，以验证以上糖酵解相关基因是否与生存获益相关；以数据库的中值风险评分作为阈值，将患者分为高风险和低风险组，构建风险模型，利用Kaplan-Meier 法绘制生存曲线评估基因特征对总体生存的预测价值；构建列线图模型来预测患者生存获益情况并进行模型验证。结果 鉴定HCC 中差异表达的糖酵解相关基因发现，与正常肝组织相比，前10 个上调基因中S100P 和SPP1 在HCC 组织中高表达，而PLA2G2A 和APOA4 在 HCC 组织中表达下调；在前10 个下调基因中，SPP2，LECT2，SLC10A1，CYP2A6，CYP3A4，HSD17B13，CYP2A7 和IYD 表达显著下调，而CYP7A1 表达在肿瘤组织中相对于正常肝组织明显上调；多因素分析结果发现高表达的SPP1，TMEM92 和EGLN3 预示着 HCC 患者的不良预后，而SPP2，LECT2，SLC10A1，CYP3A4，HSD17B13 和IYD 的高表达预测 HCC 患者的预后更佳（均P ＜0.05）；利用 LASSO 筛选确定了与 HCC 糖酵解相关的6 个差异表达基因（SPP2，LECT2，SLC10A1，CYP3A4，HSD17B13 和 IYD）；风险模型显示，随着风险评分的升高，患者生存时间呈逐渐下降趋势，随访结果为死亡的患者比例逐渐升高，两组患者中6 个基因的表达水平存在显著差异，表明它们与风险评分密切相关，是预后模型中的关键分子；生存曲线结果显示低危组患者总生存时间显著高于高危组患者，Log-Rank χ2=4.933，P ＜ 0.001；列线图预测模型中六种基因预测总分430 分，对应生存获益概率为73.98%，经验证模型安全可靠，实用性强。结论 通过评估晚期HCC 患者经PD-1 抑制剂治疗后糖酵解相关基因水平以及风险评分建立了列线图预测模型，揭示糖酵解相关基因可以预测HCC患者的生存获益状况，对患者的预后有一定的指示意义。
Abstract:
Objective To construct a risk scoring model based on glycolytic genes and predict the survival benefits of advanced hepatocellular carcinoma (HCC) patients treated with programmed cell death protein 1 (PD-1) inhibitors. Methods Clinical data and high-throughput sequencing data of 369 HCC patients receiving PD-1 inhibitor and 50 normal liver tissues were selected from the cancer genome atlas (TCGA). The patients were 53 ～ 72（69.23±6.61） years old. “limma” R package was used for differential analysis, and the abnormal expression of glycolytis-related genes in hepatocellular carcinoma tissues was screened out, and the obtained genes were analyzed by COX multivariate regression. LASSO analysis was used to screen key predictors to verify whether the above glycolytis-related genes were associated with survival benefits. With the median risk score of the database as the threshold, patients were divided into high risk and low risk groups. A risk model was constructed, and Kaplan-Meier method was used to draw a survival curve to evaluate the predictive value of genetic characteristics on overall survival. A line graph model was constructed to predict the survival benefits of patients and the model was verified. Results Compared with normal liver tissues, the first 10 up-regulated genes S100P and SPP1 were highly expressed in HCC tissues, while PLA2G2A and APOA4 were down-regulated in HCC tissues. Among the top 10 down-regulated genes, the expressions of SPP2, LECT2, SLC10A1, CYP2A6, CYP3A4, HSD17B13, CYP2A7 and IYD were significantly down-regulated, while the expression of CYP7A1 was significantly up-regulated in tumor tissues compared with normal liver tissues. Multivariate analysis showed that high expression of SPP1, TMEM92 and EGLN3 predicted poor prognosis of HCC patients, while high expression of SPP2, LECT2, SLC10A1, CYP3A4, HSD17B13 and IYD predicted better prognosis of HCC patients (all P <0.05). Six differentially expressed genes (SPP2, LECT2, SLC10A1, CYP3A4, HSD17B13 and IYD) related to HCC glycolysis were identified by LASSO screening. The risk model showed that with the increase of risk score, the survival time of patients showed a gradual downward trend, and the proportion of patients who died as a result of follow-up gradually increased. There were significant differences in the expression levels of 6 genes between the two groups of patients, indicating that they were closely related to risk score and were key molecules in the prognosis model. The survival curve showed that the total survival time of low-risk group was significantly higher than that of high-risk group (Log-Rank χ2 = 4.933, P < 0.001). The total score of the six genes predicted in the line graph prediction model was 430, and the survival benefit probability was 73.98%, which proved that the model was safe, reliable and practical. Conclusion By evaluating the level of glycolytic-related genes and risk scores in advanced stage HCC patients treated with PD-1 inhibitors, a line graph prediction model was established, revealing that glycoly-related genes can predict the survival benefit of HCC patients, which has certain indicative significance for the prognosis of patients.

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备注/Memo

备注/Memo:
作者简介：吴翠婷（1992-），女，本科，药师，研究方向：药学，E-mail：swrhip@httpnet-163.com.cn。
更新日期/Last Update: 2023-09-15