Identifying novel candidate biomarkers of RCC based on WGCNA analysis

Jin Deng, Wei Kong, Xiaoyang Mou, Shuaiqun Wang, Weiming Zeng

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)381-394
Number of pages14
JournalPersonalized Medicine
Volume15
Issue number5
DOIs
StatePublished - Sep 1 2018

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Pharmacology

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