Suppr超能文献

基于综合泛癌生物信息学分析鉴定与细胞外囊泡相关的生物标志物。

Identification of biomarkers associated with extracellular vesicles based on an integrative pan-cancer bioinformatics analysis.

机构信息

Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200025, People's Republic of China.

Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200025, People's Republic of China.

出版信息

Med Oncol. 2020 Aug 4;37(9):79. doi: 10.1007/s12032-020-01404-7.

Abstract

Extracellular vesicle (EV) has received increasing attention over the last decade. However, biomarkers and mechanisms underlying remain largely limited. Three microarray profiles, GSE78718 (K562 leukemia cell line), GSE45301 (U87-MG glioblastoma cell line), and GSE9589 (SW480 colon cancer cell line), were analyzed for the overlapped differentially expressed genes (DEGs). SurvExpress was used for the prognostic analysis of hub genes signature. Predicted transcription factors networks were built by NetworkAnalysis. Characterization between hub genes and immune cells was analyzed by the tumor immune estimation resources (TIMER) and single-sample gene set enrichment analysis (ssGSEA). The most significantly enriched pathway was lysosome. Hub genes included lysosomal-associated membrane protein 1 (LAMP1), heat shock protein family A (Hsp70) member 5 (HSPA5), lysosomal-associated membrane protein 2 (LAMP2), integrin subunit alpha V (ITGAV), and transmembrane protein 30A (TMEM30A). Significant prognostic values of hub genes signature were identified in glioblastoma (P-value = 0.006), but not colon cancer. In colon cancer, ITGAV displayed remarkably high correlation with tumor immune infiltrating cells. In glioblastoma, the highest correlation was found between HSPA5 and dendritic cell. Moreover, distinct association of immune cells between cell and EV were identified via ssGSEA. This study identified biomarkers in EV with potential immunological insights and clinical values.

摘要

细胞外囊泡 (EV) 在过去十年中受到了越来越多的关注。然而,其潜在的生物标志物和机制仍在很大程度上受到限制。分析了三个微阵列谱,GSE78718(K562 白血病细胞系)、GSE45301(U87-MG 神经胶质瘤细胞系)和 GSE9589(SW480 结肠癌细胞系),以寻找重叠的差异表达基因(DEG)。SurvExpress 用于关键基因特征的预后分析。通过 NetworkAnalysis 构建预测转录因子网络。通过肿瘤免疫估计资源 (TIMER) 和单样本基因集富集分析 (ssGSEA) 分析关键基因与免疫细胞之间的关系。最显著富集的途径是溶酶体。关键基因包括溶酶体相关膜蛋白 1(LAMP1)、热休克蛋白家族 A(Hsp70)成员 5(HSPA5)、溶酶体相关膜蛋白 2(LAMP2)、整合素亚基αV(ITGAV)和跨膜蛋白 30A(TMEM30A)。关键基因特征在神经胶质瘤中具有显著的预后价值(P 值=0.006),但在结肠癌中没有。在结肠癌中,ITGAV 与肿瘤免疫浸润细胞显示出显著的高相关性。在神经胶质瘤中,HSPA5 与树突状细胞之间的相关性最高。此外,通过 ssGSEA 还鉴定了细胞和 EV 之间免疫细胞的不同关联。这项研究确定了 EV 中的生物标志物,具有潜在的免疫学见解和临床价值。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验