鉴定与膀胱癌复发相关的 mRNA。

Identifying the mRNAs associated with Bladder cancer recurrence.

机构信息

Department of Urology, First Affiliated Hospital of Jiamusi University, Jiamusi City, Heilongjiang, China.

Department of Urology, Hongqi Hospital Affiliated to Mudanjiang Medical College, Mudanjiang City, Heilongjiang, China.

出版信息

Cancer Biomark. 2020;28(4):429-437. doi: 10.3233/CBM-190617.

DOI:10.3233/CBM-190617

PMID:32390597

Abstract

OBJECTIVE

To identify the mRNAs associated with bladder cancer (BC) recurrence.

METHODS

The transcription profile of GSE31684 including 39 recurrent BC tumor samples and 54 non-recurrent BC tumor samples as well as transcription profile of GSE13507 including 36 recurrent BC tumor samples and 67 non-recurrent BC tumor samples were downlaoded from the Gene Expression Omnibus. Then, the differentially expressed genes (DEGs) were identified using linear models for microarray data (limma) and the intersections of DEGs from the two datasets were further screened. The weighed gene co-expression network analysis (WGCNA) was used to screen the modules related to BC recurrence. Protein-protein interaction (PPI) network analysis was used to analyze the genes interaction. Their functions were predicted by Gene Ontology and KEGG pathway enrichment. Moreover, The Comparative Toxicogenomics Database 2017 update (CTD) was used to search the BC related pathway. The univariate cox regression analysis was used to identify DEGs associated to the recurrence. Kaplan-Meier plots were used to illustrate recurrence free survival time (RFS).

RESULTS

A total of 692 intersections DEGs were screened. WGCNA showed that 7 modules (2279 genes) were stable in both the datasets. A total of 169 intersection DEGs were mapped to the 7 modules. There existed 149 interaction relationships among 81 proteins (18 down-regulated and 63 up-regulated DEGs) in the PPI network. Two KEGG pathways including Focal adhesion and ECM-receptor interaction were enriched which were also found in the CTD. The univariate cox regression analysis showed that 3 DEGs (COL4A1, COL1A2 and COL5A1) were significant related to the prognosis. Multivariate cox regression analysis revealed that pathologic_N (N0-N1 vs N2-N3, p= 0.033) were independent prognostic factors for overall survival in patients with BC.

CONCLUSION

COL4A1, COL1A2 and COL5A1 could be associated with BC recurrence.

摘要

目的

鉴定与膀胱癌（BC）复发相关的 mRNAs。

方法

从基因表达综合数据库（GEO）下载 GSE31684 转录谱，包括 39 例复发性 BC 肿瘤样本和 54 例非复发性 BC 肿瘤样本，以及 GSE13507 转录谱，包括 36 例复发性 BC 肿瘤样本和 67 例非复发性 BC 肿瘤样本。然后，使用线性模型对微阵列数据（limma）进行分析，鉴定差异表达基因（DEGs），并进一步筛选两个数据集之间的 DEGs 交集。使用加权基因共表达网络分析（WGCNA）筛选与 BC 复发相关的模块。通过蛋白质-蛋白质相互作用（PPI）网络分析分析基因之间的相互作用。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析预测其功能。此外，使用 2017 年更新的比较毒理学基因组学数据库（CTD）搜索与 BC 相关的通路。使用单因素 Cox 回归分析鉴定与复发相关的 DEGs。Kaplan-Meier 图用于说明无复发生存时间（RFS）。

结果

筛选出 692 个交集 DEGs。WGCNA 显示，两个数据集之间有 7 个（2279 个基因）稳定的模块。169 个交集 DEGs 映射到 7 个模块。在 PPI 网络中，存在 81 个蛋白质（18 个下调和 63 个上调的 DEGs）之间的 149 个相互作用关系。两个 KEGG 通路，包括粘着斑和细胞外基质受体相互作用，在 CTD 中也有发现。单因素 Cox 回归分析显示，COL4A1、COL1A2 和 COL5A1 与预后显著相关。多因素 Cox 回归分析显示，BC 患者的病理 N（N0-N1 与 N2-N3，p=0.033）是总生存的独立预后因素。