Zeng Zisan, Que Tengcheng, Zhang Jiange, Hu Yanling
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Guangxi 530021, P.R. China.
Wild Animal Rescue Center, Forestry Bureau of Guangxi, Guangxi 530021, P.R. China.
Exp Ther Med. 2014 Jan;7(1):121-130. doi: 10.3892/etm.2013.1392. Epub 2013 Nov 7.
Renal cell carcinoma (RCC) is the most lethal type of cancer in the urinary system and often presents as a metastatic disease. Furthermore, there are no effective treatments for the disease. Several studies based on gene expression profiling have been performed with the aim of gaining insights into the pathogenesis of RCC; however, few studies have investigated RCC at the pathway level to search for the possible pathways involved in clear cell RCC (CCRCC). In this study, gene set enrichment analysis (GSEA) was conducted on microarray datasets from CCRCC tissue. DAVID functional enrichment analysis was performed based on the dysregulated genes that were identified in a meta-analysis performed on the microarray datasets from CCRCC tissue. In GSEA, 17 down- and 12 upregulated pathways coexisted in six datasets. The majority of the upregulated pathways were associated with the immune system. In addition, 32 dysregulated pathways were obtained from DAVID functional enrichment analysis, based on the abnormal genes identified by meta-analysis. This study demonstrated that cross-GSEA is a useful method for exploring the critical pathways involved CCRCC; however, an individual dataset with a small sample may introduce bias. A cross-GSEA based on certain well-designed datasets may be required to further the progress made in this study, following the analysis of its results.
肾细胞癌（RCC）是泌尿系统中最致命的癌症类型，通常表现为转移性疾病。此外，该疾病尚无有效的治疗方法。为了深入了解RCC的发病机制，已经进行了多项基于基因表达谱分析的研究；然而，很少有研究在通路水平上对RCC进行研究，以寻找与透明细胞肾细胞癌（CCRCC）相关的可能通路。在本研究中，对来自CCRCC组织的微阵列数据集进行了基因集富集分析（GSEA）。基于对来自CCRCC组织的微阵列数据集进行的荟萃分析中鉴定出的失调基因，进行了DAVID功能富集分析。在GSEA中，六个数据集中共存17个下调和12个上调的通路。大多数上调的通路与免疫系统相关。此外，基于荟萃分析鉴定出的异常基因，从DAVID功能富集分析中获得了32个失调的通路。本研究表明，交叉GSEA是探索CCRCC相关关键通路的一种有用方法；然而，样本量小的单个数据集可能会引入偏差。在分析其结果之后，可能需要基于某些精心设计的数据集进行交叉GSEA，以推动本研究取得进一步进展。
