| 摘要: |
| ［摘要］ 目的 筛选肝癌早期复发相关生物标志物，分析其对肝癌患者预后预测的意义。方法 基于前期研究筛选出16个差异表达基因（DEGs），包括人类白细胞抗原-A（HLA-A）、白介素-23A（IL-23A）、肿廇蛋白P63（TP63）、花生四烯酸-15-脂加氧酶B（ALOX15B）、苯并咪唑出芽抑制解除同源物1（BUB1）、趋化因子受体2（CXCR2）、CC亚族趋化因子配体20（CCL20）、C型凝集素结构域家族4成员C（CLEC4C）、酪氨酸蛋白激酶7（PTK7）、髓过氧化物酶（MPO）、白介素-1β（IL-1β）、基质金属蛋白酶9（MMP9）、G抗原2A（GAGE2A）、G抗原2E（GAGE2E）、恶性脑肿瘤缺失蛋白1（DMBT1）、叉头框蛋白M1（FOXM1）。在癌症基因组图谱(TCGA)数据库以“TCGA-LIHC”为关键词进行检索，共获得肝癌组织374例，对照组织50例（均为癌旁组织），下载RNA数据集及对应的临床资料数据，分析DEGs在肝癌组织及癌旁组织间的表达差异。对DEGs进行基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路富集分析。基于STRING在线数据库构建蛋白互作网络(PPI)。应用R 4.1.2软件包“survminer”中的surv_cutpoint函数获取最佳截断值，并以此区分高表达组和低表达组，通过Kaplan-Meier生存曲线分析DEGs与患者生存预后的关系。通过Cox回归分析影响肝癌患者预后的因素。结果 与癌旁组织相比，肝癌组织HLA-A、IL-23A、TP63、ALOX15B、BUB1、CCL20、PTK7、MMP9、GAGE2A、DMBT1、FOXM1呈高表达，MPO、IL-1β、CXCR2、CLEC4C呈低表达，差异有统计学意义（P<0.05）。GAGE2E在肝癌组织和癌旁组织间表达差异无统计学意义（P>0.05）。GO富集分析结果显示，DEGs的生物学过程（BP）变化在中性粒细胞迁移、粒细胞趋化和中性粒细胞趋化中显著富集；细胞组分（CC）的变化主要在分泌颗粒膜、吞噬性囊泡和吞噬性囊泡膜中显著富集；分子功能（MF）变化主要在受体配体活性、细胞因子受体结合和细胞因子活性中富集。KEGG通路富集分析结果显示，DEGs主要富集于肿瘤坏死因子（TNF）信号通路、白介素-17（IL-17）信号通路和类风湿性关节炎通路。PPI分析结果显示，蛋白质-蛋白质互作关系得分排名前5的蛋白质对分别为MPO-MMP9（得分0.969）、CCL20-IL-1β（得分0.958）、CCL20-CXCR2（得分0.949）、MMP9-IL-1β（得分0.949）、IL-1β-MPO（得分0.860）。Kaplan-Meier生存曲线分析结果显示，BUB1、MMP9、CCL20、PTK7、IL-1β、FOXM1高表达组的生存预后显著优于其对应的低表达组（P<0.05）。多因素Cox回归分析结果显示，T3/T4分期、带瘤状态、FOXM1高表达是影响肝癌患者OS的独立危险因素（P<0.05）。结论 肝癌早期复发相关DEGs主要涉及炎症和免疫反应相关通路。FOXM1可作为预测肝癌患者生存预后的生物学指标。 |
| 关键词: 肝癌 早期复发 差异表达基因 生物标志物 预后 叉头框蛋白M1 |
| DOI：10.3969/j.issn.1674-3806.2025.03.09 |
| 分类号:R 735.7 |
| 基金项目:国家自然科学基金项目（编号：81360368）；广西自然科学基金项目（编号：2023GXNSFAA026121） |
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| Screening of biomarkers related to early recurrence of hepatocellular carcinoma and their significance in predicting the patients′ prognosis |
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LIANG Meng1,2, CHEN Kehe1,2, CAO Yuhua2, PAN Deng2, WANG Junping2, OU Mei2, ZHONG Wenhe2, GAO Ting2, WEI Haiming2
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1.Guangxi University of Chinese Medicine, Nanning 530200, China; 2.Chemotherapy Ward 2, Clinical Oncology Center, the People′s Hospital of Guangxi Zhuang Autonomous Region(Guangxi Academy of Medical Sciences), Nanning 530021, China
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| Abstract: |
| ［Abstract］ Objective To screen the biomarkers related to early recurrence of hepatocellular carcinoma(HCC) and to analyze their significance in predicting the HCC patients′ prognosis. Methods Based on the previous studies, 16 differentially expressed genes(DEGs) were screened, including human leukocyte antigen-A(HLA-A), interleukin-23 alpha(IL-23A), tumor protein 63(TP63), arachidonate 15-lipoxygenase type B(ALOX15B), budding uninhibited by benzimidazoles 1(BUB1), C-X-C motif chemokine receptor 2(CXCR2), C-C motif chemokine ligand 20(CCL20), C-type lectin domain family 4 member C(CLEC4C), protein tyrosine kinase 7(PTK7), myeloperoxidase(MPO), interleukin-1 beta(IL-1β), matrix metallopeptidase 9(MMP9), G antigen 2A(GAGE2A), G antigen 2E(GAGE2E), deleted in malignant brain tumors 1(DMBT1), and forkhead box M1(FOXM1). The Cancer Genome Atlas(TCGA) database was searched with the keyword “TCGA-LIHC”, and a total of 374 hepatocellular carcinoma tissues and 50 control tissues(all belonging to cancer-adjacent tissues) were obtained. The RNA databases and their clinical data were downloaded. The expression differences of DEGs in the hepatocellular carcinoma tissues and the cancer-adjacent tissues were analyzed. Gene Ontology(GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed on the DEGs. A protein-protein interaction networks(PPI) was constructed by using the STRING online database. The surv_cutpoint function in the R 4.1.2 software package “survminer” was applied to obtain the optimum cut-off value, and the the optimum cut-off value was used to distinguish the high expression group from the low expression group. The relationship between the DEGs and the patients′ survival prognosis was analyzed by using Kaplan-Meier survival curves. Cox regression was used to analyze the factors affecting the HCC patients′ prognosis. Results Compared with those in the cancer-adjacent tissues, HLA-A, IL-23A, TP63, ALOX15B, BUB1, CCL20, PTK7, MMP9, GAGE2A, DMBT1 and FOXM1 in the hepatocellular carcinoma tissues were highly expressed, while MPO, IL-1β, CXCR2 and CLEC4C in the hepatocellular carcinoma tissues were low expressed, and the differences were statistically significant(P<0.05). There was no significant difference in the expression of GAGE2E between the hepatocellular carcinoma tissues and the cancer-adjacent tissues(P>0.05). The results of GO enrichment analysis indicated that the changes in biological process(BP) of DEGs were significantly enriched in neutrophil migration, granulocyte chemotaxis and neutrophil chemotaxis. The changes in cellular components(CC) were predominantly enriched in secretory granule membranes, phagocytic vesicles and phagocytic vesicle membranes. The changes in molecular functions(MF) were enriched in receptor-ligand activity, cytokine receptor binding and cytokine activity. The results of KEGG pathway enrichment analysis revealed that the DEGs were primarily enriched in the tumor necrosis factor(TNF) signaling pathway, interleukin-17(IL-17) signaling pathway and rheumatoid arthritis pathway. The results of PPI analysis showed that the top 5 protein pairs with the highest protein-protein interaction scores were MPO-MMP9(scores: 0.969), CCL20-IL-1β(scores: 0.958), CCL20-CXCR2(scores: 0.949), MMP9-IL-1β(scores: 0.949), and IL-1β-MPO(scores: 0.860). The results of Kaplan-Meier survival curve analysis indicated that the survival prognoses of the high expression groups of BUB1, MMP9, CCL20, PTK7 IL-1β and FOXM1 were significantly better than those of their corresponding low expression groups(P<0.05). The results of multivariate Cox regression analysis indicated that T3/T4 stage, tumor-bearing status and high FOXM1 expression were independent risk factors for overall survival(OS) of the HCC patients(P<0.05). Conclusion DEGs associated with early recurrence of HCC are mainly involved in the pathways related to inflammation and immune responses. FOXM1 may serve as a biological marker for predicting the survival prognosis of the HCC patients. |
| Key words: Hepatocellular carcinoma(HCC) Early recurrence Differentially expressed genes(DEGs) Biomarker Prognosis Forkhead box M1(FOXM1) |
