背景:肝细胞癌(HCC)是全球癌症死亡的主要原因,转移是早期复发和预后不良的主要原因。然而,转移的机制仍然知之甚少。
目的:探讨影响肝癌转移的可能机制,为肝癌的治疗提供可能的理论依据。
方法:通过基因芯片和生物信息学分析筛选候选分子卵磷脂胆固醇酰基转移酶(LCAT)。通过定量实时聚合酶链反应和蛋白质印迹检测临床队列样品中LCAT的表达水平。扩散,迁移,侵袭和肿瘤形成能力通过细胞计数试剂盒-8,Transwell细胞迁移,入侵,和克隆形成试验,分别。在LCAT基因敲低或过表达后,在裸鼠中检测到肿瘤形成。Ki67,E-cadherin,N-钙黏着蛋白,在肝组织中进行基质金属蛋白酶9和血管内皮生长因子,以评估LCAT对HCC的影响。用GSEA版本3.0分析各种基因标记的基因集富集分析(GSEA)。三种机器学习算法(随机森林,支持向量机,和逻辑回归)用于预测癌症基因组图谱和GEO数据库中的HCC转移。
结果:通过在HCC组织中使用基因微阵列将LCAT鉴定为与HCC转移相关的新基因。LCAT在HCC组织中显著下调,这与复发有关,肝癌患者的转移和不良预后。功能分析显示LCAT抑制肝癌细胞增殖,在体外和体内迁移和侵袭。临床病理数据显示,LCAT与HCC大小和转移呈负相关(HCC大小≤3cmvs3-9cm,P<0.001;3-9厘米vs>9厘米,P<0.01;无转移HCC与肝外转移性HCC,P<0.05)。LCAT抑制了增长,通过PI3K/AKT/mTOR信号传导肝癌细胞系的迁移和侵袭。我们的结果表明,基于LCAT的逻辑回归模型,HCC患者的TNM分期和血清甲胎蛋白水平可以有效预测高转移风险的HCC患者。
结论:LCAT在HCC的翻译和蛋白质水平下调,可能通过减弱PI3K/AKT/mTOR信号抑制肿瘤转移。LCAT是HCC的预后标志物和潜在治疗靶点。
BACKGROUND: Hepatocellular carcinoma (HCC) is a major cause of cancer mortality worldwide, and metastasis is the main cause of early recurrence and poor prognosis. However, the mechanism of metastasis remains poorly understood.
OBJECTIVE: To determine the possible mechanism affecting HCC metastasis and provide a possible theoretical basis for HCC treatment.
METHODS: The candidate molecule lecithin-cholesterol acyltransferase (LCAT) was screened by gene microarray and bioinformatics analysis. The expression levels of LCAT in clinical cohort samples was detected by quantitative real-time polymerase chain reaction and western blotting. The proliferation, migration, invasion and tumor-forming ability were measured by Cell Counting Kit-8, Transwell cell migration, invasion, and clonal formation assays, respectively. Tumor formation was detected in nude mice after LCAT gene knockdown or overexpression. The immunohistochemistry for Ki67, E-cadherin, N-cadherin, matrix metalloproteinase 9 and vascular endothelial growth factor were performed in liver tissues to assess the effect of LCAT on HCC. Gene set enrichment analysis (GSEA) on various gene signatures were analyzed with GSEA version 3.0. Three machine-learning algorithms (random forest, support vector machine, and logistic regression) were applied to predict HCC metastasis in The Cancer Genome Atlas and GEO databases.
RESULTS: LCAT was identified as a novel gene relating to HCC metastasis by using gene microarray in HCC tissues. LCAT was significantly downregulated in HCC tissues, which is correlated with recurrence, metastasis and poor outcome of HCC patients. Functional analysis indicated that LCAT inhibited HCC cell proliferation, migration and invasion both in vitro and in vivo. Clinicopathological data showed that LCAT was negatively associated with HCC size and metastasis (HCC size ≤ 3 cm vs 3-9 cm, P < 0.001; 3-9 cm vs > 9 cm, P < 0.01; metastatic-free HCC vs extrahepatic metastatic HCC, P < 0.05). LCAT suppressed the growth, migration and invasion of HCC cell lines via PI3K/AKT/mTOR signaling. Our results indicated that the logistic regression model based on LCAT, TNM stage and the serum level of α-fetoprotein in HCC patients could effectively predict high metastatic risk HCC patients.
CONCLUSIONS: LCAT is downregulated at translational and protein levels in HCC and might inhibit tumor metastasis via attenuating PI3K/AKT/mTOR signaling. LCAT is a prognostic marker and potential therapeutic target for HCC.