Yan Fangrong, Wang Yue, Liu Chunhui, Zhao Huiling, Zhang Liya, Lu Xiaofan, Chen Chen, Wang Yaoyan, Lu Tao, Wang Fei
Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, P.R. China.
Zhongda Hospital Southeast University, Nanjing, P.R. China.
Oncotarget. 2017 Nov 30;8(66):110358-110366. doi: 10.18632/oncotarget.22769. eCollection 2017 Dec 15.
Clear cell renal cell carcinoma (ccRCC) is the most prominent type of kidney cancer in adults. The patients within metastatic ccRCC have a poor 5-year survival rate that is less than 10%. It is essential to identify ccRCC -related genes to help with the understanding of molecular mechanism of ccRCC. In this literature, we aim to identify genes related to ccRCC based on a gene network. We collected gene expression level data of ccRCC from the Cancer Genome Atlas (TCGA) for our analysis. We constructed a co-expression gene network as the first step of our study. Then, the network sparse boosting approach was performed to select the genes which are relevant to ccRCC. Results of our study show there are 15 genes selected from the all genes we collected. Among these genes, 7 of them have been demonstrated to play a key role in development and progression or in drug response of ccRCC. This finding offers clues of gene markers for the treatment of ccRCC.
透明细胞肾细胞癌（ccRCC）是成人中最常见的肾癌类型。转移性ccRCC患者的5年生存率很低，不到10%。识别与ccRCC相关的基因对于帮助理解ccRCC的分子机制至关重要。在本文中，我们旨在基于基因网络识别与ccRCC相关的基因。我们从癌症基因组图谱（TCGA）收集了ccRCC的基因表达水平数据用于分析。作为研究的第一步，我们构建了一个共表达基因网络。然后，采用网络稀疏增强方法来选择与ccRCC相关的基因。我们的研究结果表明，从我们收集的所有基因中选择出了15个基因。在这些基因中，有7个已被证明在ccRCC的发展、进展或药物反应中起关键作用。这一发现为ccRCC的治疗提供了基因标志物线索。
