异常纺锤体样小头畸形相关蛋白在鼻咽癌中的表达及其临床意义
Expression of abnormal spindle-like microcephaly associated protein in nasopharyngeal carcinoma and its clinical significance
杨开炎 1唐凤珠 2覃启才 1李旭祥 3冯大益 3农丰靖 1杨秋云1
作者信息
- 1. 百色市人民医院 耳鼻咽喉头颈外科,广西 百色 533000
- 2. 广西壮族自治区人民医院 耳鼻咽喉头颈外科,广西 南宁 530000
- 3. 百色市人民医院 病理科,广西 百色 533000
- 折叠
摘要
目的 通过免疫组化染色的方法研究异常纺锤体样小头畸形相关蛋白(abnormal spindle-like microcephaly associated protein,ASPM)在鼻咽癌组织样本中的表达情况,进一步分析ASPM蛋白表达与鼻咽癌患者临床病理参数和预后的关系,探讨ASPM mRNA在鼻咽癌中的表达情况.方法 从GEO数据库下载鼻咽癌的芯片数据集,使用R语言对鼻咽癌芯片数据集进行差异表达分析;使用免疫组化染色方法分析ASPM蛋白在鼻咽癌中的差异表达;使用卡方检验的方法分析ASPM表达与鼻咽癌患者临床病理参数的相关性;采用生存曲线分析ASPM表达与鼻咽癌患者预后的关系;采用Cox回归模型分析影响鼻咽癌患者预后的危险因素;使用受试者工作特征(receiver operator characteristic,ROC)曲线评估各种预后参数预测鼻咽癌患者预后的效能.结果 通过鼻咽癌芯片数据分析发现ASPM mRNA在鼻咽癌芯片数据集中高表达(P<0.001);免疫组化染色结果显示鼻咽癌组织中ASPM蛋白表达明显高于鼻咽炎组织(P<0.001),ASPM表达与T分期(P=0.048)、N分期(P=0.050)及总临床分期(P=0.029)相关,高表达ASPM蛋白组患者总生存期短于低表达ASPM蛋白组患者(P<0.001);通过多因素Cox回归模型分析,显示ASPM表达水平可能为影响鼻咽癌患者预后的独立危险因素(P=0.015);通过ROC曲线分析,显示联合总临床分期及ASPM表达用于预测鼻咽癌患者预后具有更高的准确性(P<0.001).结论 ASPM在鼻咽癌组织样本中高表达,其高表达与鼻咽癌的恶性程度、疾病进展及较差的预后相关,可能成为鼻咽癌中有价值的预测预后的生物标志物.联合总临床分期及ASPM表达用于预测鼻咽癌患者预后可能是一种有前景的方法.
Abstract
Objective This paper investigated the expression of abnormal spindle-like microcephaly associated protein(ASPM)in nasopharyngeal carcinoma tissue samples using immunohistochemical staining,and further analyzed the relationship between ASPM protein expression and clinicopathological parameters and the prognosis of patients with nasopharyngeal carcinoma,and then dis-cussed the expression of ASPM mRNA in nasopharyngeal carcinoma.Methods The microarray dataset of nasopharyngeal carcino-ma was downloaded from the GEO database,and the differential expression of the nasopharyngeal carcinoma microarray dataset was analyzed using R language.The differential expression of ASPM protein in nasopharyngeal carcinoma was analyzed using immuno-histochemical staining,the correlation between ASPM expression and clinicopathological parameters of patients with nasopharyngeal carcinoma was analyzed using the chi-square test,the relationship between ASPM expression and prognosis of patients with nasopha-ryngeal carcinoma was analyzed by survival curves,the risk factors affecting prognosis of patients with nasopharyngeal carcinoma were analyzed using the Cox regression model,and the receiver operator characteristic(ROC)curve was used to evaluate the per-formance of various prognostic parameters in predicting the prognosis of patients with nasopharyngeal carcinoma.Results ASPM mRNA was found to be highly expressed in nasopharyngeal carcinoma microarray data set through analysis of nasopharyngeal carci-noma microarray data(P<0.001).Immunohistochemical staining showed that expression of ASPM in nasopharyngeal carcinoma tis-sues was significantly higher than in nasopharyngitis tissues(P<0.001).ASPM expression correlated with T stage(P=0.048),N stage(P=0.050),and total clinical stage(P=0.029).The overall survival time of the high expression ASPM protein group was shorter than that of the low expression ASPM protein group(P<0.001).Multivariate Cox regression model analysis showed that AS-PM expression level may be an independent risk factor affecting prognosis of patients with nasopharyngeal carcinoma(P=0.015).ROC curve analysis showed that total clinical stage combined with ASPM expression achieved a higher accuracy in predicting prog-nosis of patients with nasopharyngeal carcinoma(P<0.001).Conclusion ASPM is highly expressed in nasopharyngeal carcinoma tissue samples,and this high expression is related to malignancy,disease progression,and poor prognosis of nasopharyngeal carcino-ma,and may become a valuable biomarker for predicting prognosis in nasopharyngeal carcinoma.Combining total clinical stage and ASPM expression may be a promising method for predicting prognosis of patients with nasopharyngeal carcinoma.
关键词
鼻咽癌/免疫组化/肿瘤预后/异常纺锤体样小头畸形相关蛋白/差异表达Key words
Nasopharyngeal carcinoma/Immunohistochemistry/Tumor prognosis/Abnormal spindle-like microcephaly associated protein/Differential expression引用本文复制引用
基金项目
广西卫生健康委科研项目(Z20211109)
国家自然科学基金(82060190)
广西科技基地和人才专项(桂科AD20297069)
出版年
2024
NETL
NSTL
万方数据