Competitive Endogenous RNA Landscape in Epstein-Barr Virus Associated Nasopharyngeal Carcinoma

Abstract

Non-coding RNAs have been shown to play important regulatory roles, notably in cancer development. In this study, we investigated the role of microRNAs and circular RNAs in Nasopharyngeal Carcinoma (NPC) by constructing a circRNA-miRNA-mRNA co-expression network and performing differential expression analysis on mRNAs, miRNAs, and circRNAs. Specifically, the Epstein-Barr virus (EBV) infection has been found to be an important risk factor for NPC, and potential pathological differences may exist for EBV+ and EBV- subtypes of NPC. By comparing the expression profile of non-cancerous immortalized nasopharyngeal epithelial cell line and NPC cell lines, we identified differentially expressed coding and non-coding RNAs across three groups of comparison: cancer vs. non-cancer, EBV+ vs. EBV- NPC, and metastatic vs. non-metastatic NPC. We constructed a ceRNA network composed of mRNAs, miRNAs, and circRNAs, leveraging co-expression and miRNA target prediction tools. Within the network, we identified the regulatory ceRNAs of CDKN1B, ZNF302, ZNF268, and RPGR. These differentially expressed axis, along with other miRNA-circRNA pairs we identified through our analysis, helps elucidate the genetic and epigenetic changes central to NPC progression, and the differences between EBV+ and EBV- NPC.

Comprehensive analysis of aberrantly expressed circRNAs, mRNAs and lncRNAs in patients with nasopharyngeal carcinoma

“…They constructed ceRNA and performed differential expression analysis, and they found CDKN1B, ZNF302, ZNF268, and other key differential genes. 14 In this study, we used microarrays to detect differential expression (DE) of circRNAs, mRNAs, and lncRNAs in nasopharyngeal carcinoma (NPC) tissues. We also performed network analyses (competitive endogenous RNA network analysis for circRNAs, mRNAs, and miRNAs, and co‐expression network analysis for lncRNAs and mRNAs) trying to infer the potential interactions of these functional RNAs.…”

“… 12 , 13 Because circRNAs is a kind of singled‐stranded RNA with neither 5′‐3′ polarities nor polyadenylated tails, it is refrained from exo‐nucleolytic degradation and more stable. 14 , 15 , 16 Due to those characteristics, circRNAs are regarded as a promising biomarkers. Several supporting evidences have shown that circRNAs with miRNA response elements (MREs) competitively bind to miRNAs to regulate target genes expression.…”

“…There is increasing evidence that circNRAs can be divided into noncoding circrnas and coding circrnas 12,13 . Because circRNAs is a kind of singled‐stranded RNA with neither 5′‐3′ polarities nor polyadenylated tails, it is refrained from exo‐nucleolytic degradation and more stable 14–16 . Due to those characteristics, circRNAs are regarded as a promising biomarkers.…”

Protein‐protein interaction networks as miners of biological discovery

“…In order to utilize the growingly available multi-omics data, several studies have constructed heterogenous networks combining various data types, such as phenotype ontology [105], clinical features, long non-coding RNA [106,107], and disease associations [108]. The most important step in the construction of heterogenous networks of different data types is the linkage between nodes of initially homogenous networks.…”

Construction of a competing endogenous RNA network in head and neck squamous cell carcinoma by pan-cancer analysis

“…A previous study compared the gene expression changes between NPC and noncancerous human immortalized nasopharyngeal epithelial cell lines, Epstein-Barr virus + (EBV + ) compared with Epstein-Barr virus − (EBV − ) NPC cell lines, and metastatic vs. nonmetastatic patient samples, and constructed a circRNA-miRNA-mRNA ceRNA network. By ceRNA network analysis, they successfully identified the non-coding RNA axis that was closely biologically linked with NPC tumorigenesis ( 4 ). However, the role of ceRNA network in HNSC tumorigenesis is still unclear.…”