基于 TCGA 数据库筛选、 分析并验证宫颈癌生物标志物

目的 基于生物信息学筛选分析宫颈癌差异表达基因 ( differentially expressed gene, DEGs) 及差 异表达 miRNA, 并进一步对差异基因和蛋白进行验证, 以期寻找潜在的生物标志物和治疗靶点。 方法 从 肿瘤基因组图谱 (the cancer genome atlas, TCGA) 数据库获取宫颈癌相关数据, edgeR 算法筛选 DEGs 和差 异 miRNAs。 利用 Cytoscape3. 8. 2 软件构建 mRNA-miRNA 共表达网络。 利用 DAVID 软件对 DEGs 和通过 miRWalk 网站预测的差异 miRNA 的目标基因进行 GO 富集分析和 KEGG 富集分析。 利用 qPCR 和 Western 印 迹技术对 DEGs 进行进一步验证。 结果 筛选出 149 个上调的 DEGs 和 171 个下调的 DEGs, 以及 46 个上调 的差异 miRNAs 和 64 个下调的差异 miRNAs。 DEGs 和 miRNA 目标基因在细胞组成上的富集具有一致性, 都富集在胞质、 核和核质中。 但共表达网络发现 DEGs 和差异 miRNAs 之间不存在明显的调控关系。 因此, 后续实验重点放在了对 DEGs 的验证上, 对差异表达性较为显著的 TCEAL6、 CLEC3B、 LMOD1、 CNN1 进行 了验证。 qPCR 显示它们在宫颈癌中表达量均显著降低, 符合预期, 对 CNN1 进行的 Western 印迹也显示其 在宫颈癌中的低表达。 结论 TCEAL6、 CLEC3B、 LMOD1、 CNN1 在宫颈癌中均显著低表达, 有望成为宫颈 癌生物标志物。

Screening,Analysis and Validation of Cervical Cancer Biomarkers Based on TCGA Database

Objective To analyze the differentially expressed genes (DEGs) and miRNAs of cervical cancer based on bioinformatics, and further verify the differentially expressed genes and proteins, in order to find potential biomarkers and therapeutic targets. Methods Cervical cancer related data were obtained from TCGA database, and DEGs and differential miRNAs were screened by edgeR algorithm. The mRNA-miRNA co-expression network was constructed using Cytoscape3. 8. 2 software. GO enrichment analysis and KEGG enrichment analysis were performed for DEGs and target genes of differential miRNA predicted by miRWalk website using DAVID software. DEGs was further verified by qPCR and Western blotting. Results A total of 149 up-regulatedand 171 down-regulated DEGs, 46 up-regulated differential miRNAs and 64 down-regulated differential miRNAs were screened out. The enrichments of DEGs and miRNA target genes were consistent in cell composition, and they were all enriched in cytoplasm, nucleus and cytoplasm. However, co-expression network found no significant regulatory relationship between DEGs and differential miRNAs. Therefore, we subsequently focused on the verification of DEGs, and verified TCEAL6, CLEC3B, LMOD1 and CNN1 with relatively significant differential expression. QPCR showed that the expression levels of CNN1 in cervical cancer were significantly reduced, which was in line with expectations. Western blotting analysis of CNN1 also showed that it was lowly expressed in cervical cancer. Conclusion In this study, DEGs and differentially expressed miRNAs of cervical cancer were screened and analyzed based on the TCGA database, and TCEAL6, CLEC3B, LMOD1 and CNN1were further verified. The results showed that they were significantly under-expressed in cervical cancer, which is expected to become biomarkers of cervical cancer