目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryoni...目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryonic antigen,CEA)及不同组合模式在转移性肝细胞癌诊断中的应用及评分模型的构建。方法收集2019年1月至2022年7月我院283例肺癌、肠癌患者的血清,根据是否发生肝转移分为试验组(发生肝转移,n=70)和对照组(未发生肝转移,n=213),检测血清肿瘤标记物PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平。比较各指标及其不同组合对转移性肝细胞癌筛查的敏感度、特异度,并绘制ROC曲线。通过单因素和多因素分析转移性肝细胞癌的独立影响因素,建立转移性细胞癌预测模型并验证。结果与对照组相比,试验组患者PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平显著升高,差异有统计学意义(P<0.05)。两组在结肠息肉、脂肪肝、肿瘤大小、阳性淋巴结数目等方面比较,差异有统计学意义(P<0.05)。PIVKA-Ⅱ、AFP、AFP-L3、CEA、患有结肠息肉、脂肪肝、肿瘤≥5 cm、有阳性淋巴结是转移性肝细胞癌的独立危险因素(P<0.05)。在不同的组合指标中,PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡。对进入回归方程的指标进行风险评分,其中患有结肠息肉、患有脂肪肝、肿瘤大小≥5 cm、PIVKA-Ⅱ≥40 mAU/mL、AFP≥8.3 ng/mL、AFP-L3≥10%、CEA≥5.7 ng/mL七项指标分别设定为2、2、2、3、3、1.5、3.5分。总分在1.5~17分,根据百分位数进行评分分级,低危组<7分,中危组7~12.5分,高危组>12.5分,结果显示随着评分增加,转移性肝细胞癌风险增加。结论PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡,依据转移性肝细胞癌风险预测模型制定的评分标准有良好的预测性。展开更多
本研究旨在筛选与乙肝阳性转移性肝细胞癌相关的基因并揭示其潜在的分子机制。利用GEO数据库中GSE364数据集,筛选在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因,DAVID对差异表达基因进行GO与信号通路富集分析,并用STRING和Cytosc...本研究旨在筛选与乙肝阳性转移性肝细胞癌相关的基因并揭示其潜在的分子机制。利用GEO数据库中GSE364数据集,筛选在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因,DAVID对差异表达基因进行GO与信号通路富集分析,并用STRING和Cytoscape构建蛋白互作网络,随后用mi Rwalk 2.0筛选可能参与肝细胞癌转移的miRNAs,构建miRNA-枢纽基因调控网络。之后使用Smoami R DB 2.0和c Bio Portal分析枢纽基因突变与circRNA和肝细胞癌预后的关系。我们获得在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因701个,富集分析发现这些基因主要涉及血管生成和血管内皮生长因子信号转导等信号通路。从构建的蛋白互作网络中获得参与蛋白互作模式1的15个枢纽基因,GO分析发现其主要参与RNA加工、代谢、剪接等生物过程。构建的miRNA-枢纽基因调控网络中有4个miRNA参与两个枢纽基因的调控,此外肝细胞癌中SRSF1基因有突变并可转录为hsa_circ_0044757,SNRNP200基因突变与患者预后相关。本研究发现的差异表达基因和枢纽基因,有助于我们认识乙肝相关性肝细胞癌转移的分子机制,并可作为新的用于诊断和预后判断的分子标志物。展开更多
AIM： To investigate the association of cyclooxygenase-2 （COX-2） expression with angiogenesis and the number and type of inflammatory cells （macrophages/Kupffer cells; mast cells） within primary hepatocellular car...AIM： To investigate the association of cyclooxygenase-2 （COX-2） expression with angiogenesis and the number and type of inflammatory cells （macrophages/Kupffer cells; mast cells） within primary hepatocellular carcinoma （HCC） tissues and adjacent non-tumorous （NT） tissues. METHODS： Immunohistochemistry for COX-2, CD34, CD68 and mast cell tryptase （MCT） was performed on 14 well-characterized series of liver-cirrhosis-associated HCC patients. COX-2 expression and the number of inflammatory cells in tumor lesions and surrounding liver tissues of each specimen were compared. Moreover, COX-2, CD34 staining and the number of inflammatory cells in areas with different histological degrees within each tumor sample were comparatively analyzed. RESULTS： The percentage of COX-2 positive cells was significantly higher in NT tissues than in tumors. COX-2 expression was higher in well-differentiated HCC than in poorly-differentiated tissues. Few mast cells were observed within the tumor mass, whereas a higher number was observed in the surrounding tissue, especially in peri-portal spaces of NT tissues. Abundant macrophages/ Kupffer cells were observed in NT tissues, whereas the number of cells was significantly lower in the tumor mass. However, a higher cell number was observed in the welldifferentiated tumor and progressively decreased in relation to the differentiation grade. Within the tumor, a positive correlation was found between COX-2 expression and the number of macrophages/Kupffer cells and mastcells. Moreover, there was a positive correlation between CD34 and COX-2 expression in tumor tissues. Comparison between well- and poorly-differentiated HCC showed that the number of CD34-positive cells decreased with dedifferentiation. However, COX-2 was the only independent variable showing a positive correlation with CD34 in a multivariate analysis. CONCLUSION： The presence of inflammatory cells and COX-2 expression in liver tumor suggests a possible relationship with tumor angiogenesis. COX-2 expressing cells and the number of macrophages/Kupffer cells and mast cells decrease with progression of the disease.展开更多
文摘目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryonic antigen,CEA)及不同组合模式在转移性肝细胞癌诊断中的应用及评分模型的构建。方法收集2019年1月至2022年7月我院283例肺癌、肠癌患者的血清,根据是否发生肝转移分为试验组(发生肝转移,n=70)和对照组(未发生肝转移,n=213),检测血清肿瘤标记物PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平。比较各指标及其不同组合对转移性肝细胞癌筛查的敏感度、特异度,并绘制ROC曲线。通过单因素和多因素分析转移性肝细胞癌的独立影响因素,建立转移性细胞癌预测模型并验证。结果与对照组相比,试验组患者PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平显著升高,差异有统计学意义(P<0.05)。两组在结肠息肉、脂肪肝、肿瘤大小、阳性淋巴结数目等方面比较,差异有统计学意义(P<0.05)。PIVKA-Ⅱ、AFP、AFP-L3、CEA、患有结肠息肉、脂肪肝、肿瘤≥5 cm、有阳性淋巴结是转移性肝细胞癌的独立危险因素(P<0.05)。在不同的组合指标中,PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡。对进入回归方程的指标进行风险评分,其中患有结肠息肉、患有脂肪肝、肿瘤大小≥5 cm、PIVKA-Ⅱ≥40 mAU/mL、AFP≥8.3 ng/mL、AFP-L3≥10%、CEA≥5.7 ng/mL七项指标分别设定为2、2、2、3、3、1.5、3.5分。总分在1.5~17分,根据百分位数进行评分分级,低危组<7分,中危组7~12.5分,高危组>12.5分,结果显示随着评分增加,转移性肝细胞癌风险增加。结论PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡,依据转移性肝细胞癌风险预测模型制定的评分标准有良好的预测性。
文摘本研究旨在筛选与乙肝阳性转移性肝细胞癌相关的基因并揭示其潜在的分子机制。利用GEO数据库中GSE364数据集,筛选在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因,DAVID对差异表达基因进行GO与信号通路富集分析,并用STRING和Cytoscape构建蛋白互作网络,随后用mi Rwalk 2.0筛选可能参与肝细胞癌转移的miRNAs,构建miRNA-枢纽基因调控网络。之后使用Smoami R DB 2.0和c Bio Portal分析枢纽基因突变与circRNA和肝细胞癌预后的关系。我们获得在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因701个,富集分析发现这些基因主要涉及血管生成和血管内皮生长因子信号转导等信号通路。从构建的蛋白互作网络中获得参与蛋白互作模式1的15个枢纽基因,GO分析发现其主要参与RNA加工、代谢、剪接等生物过程。构建的miRNA-枢纽基因调控网络中有4个miRNA参与两个枢纽基因的调控,此外肝细胞癌中SRSF1基因有突变并可转录为hsa_circ_0044757,SNRNP200基因突变与患者预后相关。本研究发现的差异表达基因和枢纽基因,有助于我们认识乙肝相关性肝细胞癌转移的分子机制,并可作为新的用于诊断和预后判断的分子标志物。
基金Supported by the MIUR and Progetto Strategico Oncologia "Terapia Preclinica Moleculare Oncologia" MIUR-CNR
文摘AIM： To investigate the association of cyclooxygenase-2 （COX-2） expression with angiogenesis and the number and type of inflammatory cells （macrophages/Kupffer cells; mast cells） within primary hepatocellular carcinoma （HCC） tissues and adjacent non-tumorous （NT） tissues. METHODS： Immunohistochemistry for COX-2, CD34, CD68 and mast cell tryptase （MCT） was performed on 14 well-characterized series of liver-cirrhosis-associated HCC patients. COX-2 expression and the number of inflammatory cells in tumor lesions and surrounding liver tissues of each specimen were compared. Moreover, COX-2, CD34 staining and the number of inflammatory cells in areas with different histological degrees within each tumor sample were comparatively analyzed. RESULTS： The percentage of COX-2 positive cells was significantly higher in NT tissues than in tumors. COX-2 expression was higher in well-differentiated HCC than in poorly-differentiated tissues. Few mast cells were observed within the tumor mass, whereas a higher number was observed in the surrounding tissue, especially in peri-portal spaces of NT tissues. Abundant macrophages/ Kupffer cells were observed in NT tissues, whereas the number of cells was significantly lower in the tumor mass. However, a higher cell number was observed in the welldifferentiated tumor and progressively decreased in relation to the differentiation grade. Within the tumor, a positive correlation was found between COX-2 expression and the number of macrophages/Kupffer cells and mastcells. Moreover, there was a positive correlation between CD34 and COX-2 expression in tumor tissues. Comparison between well- and poorly-differentiated HCC showed that the number of CD34-positive cells decreased with dedifferentiation. However, COX-2 was the only independent variable showing a positive correlation with CD34 in a multivariate analysis. CONCLUSION： The presence of inflammatory cells and COX-2 expression in liver tumor suggests a possible relationship with tumor angiogenesis. COX-2 expressing cells and the number of macrophages/Kupffer cells and mast cells decrease with progression of the disease.
