Jin Deng1, Wei Kong1, Xiaoyang Mou2, Shuaiqun Wang1, Weiming Zeng1. 1. College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai 201306, PR China. 2. Department of Biochemistry, Rowan University & Guava Medicine, Glassboro, NJ 08028, USA.
Abstract
AIM: Extracting differential expression genes (DEGs) is an effective approach to improve the accuracy of determining the candidate biomarker genes. However, the previous DEGs analysis methods ignore that the expression levels of genes in different pathology stages of cancers are complex and various. METHODS: In our study, staging DEGs analysis and weighted gene co-expression network analysis were applied to gene expression data of renal cell carcinoma (RCC). RESULTS: According to construct gene topology network for exploring hub genes, 12 genes were identified as hub genes. CONCLUSION: Combining with the effect of hub gene expression level on RCC patient survival and different biological data analysis, three hub genes were found that they might be three novel candidate biomarkers of RCC.
AIM: Extracting differential expression genes (DEGs) is an effective approach to improve the accuracy of determining the candidate biomarker genes. However, the previous DEGs analysis methods ignore that the expression levels of genes in different pathology stages of cancers are complex and various. METHODS: In our study, staging DEGs analysis and weighted gene co-expression network analysis were applied to gene expression data of renal cell carcinoma (RCC). RESULTS: According to construct gene topology network for exploring hub genes, 12 genes were identified as hub genes. CONCLUSION: Combining with the effect of hub gene expression level on RCCpatient survival and different biological data analysis, three hub genes were found that they might be three novel candidate biomarkers of RCC.
Authors: Jéssica Almeida Batista-Gomes; Fernando Augusto Rodrigues Mello; Edivaldo Herculano Corrêa de Oliveira; Michel Platini Caldas de Souza; Alayde Vieira Wanderley; Laudreisa da Costa Pantoja; Ney Pereira Carneiro Dos Santos; Bruna Cláudia Meireles Khayat; André Salim Khayat Journal: Mol Cytogenet Date: 2020-06-26 Impact factor: 2.009