Exploring functions of long noncoding RNAs across multiple cancers through co-expression network

In contrast to protein-coding genes, long-noncoding RNAs (lncRNAs) are much less well understood, despite increasing evidence indicating a wide range of their biological functions, and possible roles in various cancers. Based on public RNA-seq datasets of four solid cancer types, researchers from Sichuan University utilize Weighted Correlation Network Analysis (WGCNA) to propose a strategy for exploring the functions of lncRNAs altered in more than two cancer types, which they call onco-lncRNAs. Results indicate that cancer-expressed lncRNAs show high tissue specificity and are weakly expressed, more so than protein-coding genes. Most of the 236 onco-lncRNAs the researchers identified have not been reported to have associations with cancers before. Their analysis exploits co-expression network to reveal that onco-lncRNAs likely play key roles in the multistep development of human cancers, covering a wide range of functions in genome stability maintenance, signaling, cell adhesion and motility, morphogenesis, cell cycle, immune and inflammatory response. These observations contribute to a more comprehensive understanding of cancer-associated lncRNAs, while demonstrating a novel and efficient strategy for subsequent functional studies of lncRNAs.

Network and expression levels of 51 top hub genes in brown module

(a) Cytoscape network visualization of 51 genes, in which only edges with weight (w) above a threshold of 0.2 are displayed. The red nodes denote lncRNA genes. The green and blue nodes both denote protein-coding genes, but the green color stands for genes with function in maintaining genomic stability. (b) The expression levels of 51 genes in each cancer type. The y axis represents the average FPKM value of samples in each group. And the blue and red colors denote protein-coding genes and onco-lncRNAs, respectively.

Li S, Li B, Zheng Y, Li M, Shi L, Pu X. (2017) Exploring functions of long noncoding RNAs across multiple cancers through co-expression network. Sci Rep 7(1):754.[article]

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