| 引用本文: | 余娟,林青青,秦燕,秦爽,魏星.浆液性卵巢癌铁死亡关键基因的筛选及生物信息学分析[J].生物信息学,2024,22(2):148-158. |
| YU Juan,LIN Qingqing,QIN Yan,QIN Shuang,WEI Xing.Screening and bioinformatics analysis of key genes for ferroptosis in serous ovarian cancer[J].Chinese Journal of Bioinformatics,2024,22(2):148-158. |
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| 浆液性卵巢癌铁死亡关键基因的筛选及生物信息学分析 |
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余娟1,林青青2,秦燕1,秦爽1,魏星1
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(1.成都医学院附属第三医院,成都市郫都区人民医院,成都 611730;2.绵阳市人民医院,四川 绵阳 621000)[HJ1.5mm]
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| 摘要: |
| 利用生物信息学方法筛选浆液性卵巢癌相关铁死亡关键基因,并预测其生物学功能。从GEO数据库中获得有关浆液性卵巢癌的数据集GSE54388和GSE12470,采用R语言中的“Limma”包分析挑选浆液性卵巢癌上皮组织与正常卵巢上皮组织中差异表达基因,绘制火山图、热图。利用Venn软件在线工具绘制GSE54388,GSE12470,FerrDb三个数据集韦恩图。对相关基因进行功能富集分析、蛋白互作分析、生存分析,对关键基因绘制ROC曲线进行诊断分析。采用GEPIA2 数据库对筛选基因进行验证,并进行免疫浸润分析。结果发现:从GSE54388中筛选出2458个差异基因,其中上调1309个,下调1149个。从GSE12470中筛选出3534个差异基因,其中上调1 837个,下调1 697个。与铁死亡基因数据集取交集,共得到16个差异基因,蛋白互作网络筛选出7个基因构建的关键模块,绘制生存曲线发现浆液性卵巢癌患者中5个基因与患者总生存率不良相关,其中NRAS,PSAT1,CDKN2A,GDF15这4个基因高表达,CAV1低表达。ROC曲线显示这5个基因中CAV1,NRAS,PSAT1的AUC诊断曲线面积大于0.95,有较高的诊断价值。GEPIA2 数据库验证发现5个基因的表达情况与预测相符,仅NRAS基因表达在浆液性卵巢癌患者Ⅱ期、Ⅲ期、Ⅳ期有显著差异(P<0.05)。免疫浸润分析发现CDKN2A表达与aDC细胞浸润水平呈正相关(P<0.05,spearman相关系数0.353)；CAV1表达与Mast细胞浸润正向关(P<0.05,spearman相关系数0.327)；NRAS与T helper细胞浸呈正向关(P<0.05,spearman相关系数0.362)。通过生物信息学方法筛选出与浆液性卵巢癌铁死亡相关的5个基因CAV1,NRAS,PSAT1,CDKN2A,GDF15,可能在浆液性卵巢癌的发生发展中起重要作用,有望成为该病诊断、治疗和预后的潜在分子生物标志物。 |
| 关键词: 浆液性卵巢癌 铁死亡 关键基因 生物信息学 |
| DOI：10.12113/202210021 |
| 分类号:Q3 |
| 文献标识码:A |
| 基金项目:成都市郫都区人民医院-成都医学院联合科研基金护理专项(No.2021LHHL-12); 成都医学院校级课题(No.CYZYB20-23),成都市卫健委2021年课题(No.2021139);2021年四川省医学会青年创新科研课题(No.Q21094). |
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| Screening and bioinformatics analysis of key genes for ferroptosis in serous ovarian cancer |
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YU Juan1, LIN Qingqing2, QIN Yan1, QIN Shuang1, WEI Xing1
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(1.The Third Affiliated Hospital of Chengdu Medical College,Peoples Hospital of Chengdus Pidu District,Chengdu 611730,China; 2. Peoples Hospital of Mianyang City, Mianyang 621000, Sichuan,China)
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| Abstract: |
| To screen key iron death genes associated with plasmacytotic ovarian cancer and predict their biological functions using bioinformatics. The datasets GSE54388 and GSE12470 are obtained from the GEO database on plasmacytotic ovarian cancer, and the “limma” package in R language is used to analyze and select differentially expressed genes in epithelial tissues of plasmacytotic ovarian cancer and normal ovarian epithelial tissues, and to plot volcanoes and heat maps, and Venn software online The Venn software online tool is used to draw Venn diagrams for GSE54388, GSE12470 and FerrDb, and to perform functional enrichment analysis, protein interaction analysis, survival analysis, ROC curves for key genes for diagnostic analysis, validation of the screened genes using GEPIA2 database, and immuno-infiltration analysis. 2458 differential genes are screened from GSE54388, of which 1309 are up-regulated and 1149 are down-regulated, 3534 differential genes are screened from GSE12470, of which 1837 are up-regulated and 1697 are down-regulated, and intersect with the iron death gene dataset to obtain a total of 16 differential genes, and the protein interaction network screen 7 key modules of gene constructs. The survival curve is plotted and found that 5 genes are associated with poor overall survival in patients with plasmacytotic ovarian cancer, among which 4 genes, NRAS,PSAT1,CDKN2A,GDF15, are highly expressed and CAV1is lowly expressed. ROC curve shows that the AUC diagnostic curve area of CAV1, NRAS,PSAT1among these 5 genes is greater than 0.95, which has high diagnostic value. The GEPIA2 database validation reveal that the expression of the 5 genes is consistent with the prediction, Only the expression of NRASgene is significantly different in serous ovarian cancer patients at stage Ⅱ, Ⅲ and Ⅳ (P<0.05), immunoinfiltration analysis showed that CDKN2A expression is positively correlated with the infiltration level of aDC cells (P<0.05, spearman correlation coefficient 0.353), CAV1expression is positively correlated with Mast cell infiltration (P<0.05, spearman correlation coefficient 0.327), NRASis positively correlated with T helper cell leaching (P<0.05, spearman correlation coefficient 0.362). Five genes associated with iron death in plasmacytotic ovarian cancer: CAV1,NRAS,PSAT1,CDKN2A,GDF15are screened by bioinformatics methods, which may play an important role in the development of plasmacytotic ovarian cancer and have the potential to become molecular biomarkers for the diagnosis,treatment and prognosis of this disease. |
| Key words: Serous ovarian cancer Ferroptosis Key genes Bioinformatics |
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