Heterogeneous expression of long noncoding RNA RP11-109D20.2: Insights into regulatory gene expression roles in colon cancer

Abstract

Objectives: Colorectal cancer is one of the deadliest cancers worldwide, which can be prevented and even cured by early diagnosis and more efficient treatment modalities. Comprehensive transcriptional analysis has highlighted the importance of lncRNAs in CRC tumorigenesis. In this study, we identified co-expressed lncRNA networks based on public RNA sequencing data for biomarker prediction in CRC and then verified the best candidate experimentally.

Materials and methods: Publicly available RNA-sequencing data (BioProject PRJEB27536) of CRC samples and normal adjacent tissues were reanalyzed using the DESeq2 package in R to find differentially expressed lncRNAs. Pathway enrichment and gene network analysis were accomplished using GSEA and WGCNA to identify potential functions of lncRNAs with possible roles in tumorigenesis pathways. Subsequently, the expression of RP11-109D20.2 (lnc-Duox2-1:1) was assessed in fresh/frozen tissues obtained from 46 CRC patients by quantitative RT-PCR.

Results: A total of 17939 DElncRNAs were identified between CRC and normal tissues via bioinformatics analyses. A significant up-regulation of RP11-109D20.2 (48%) was observed in CRC samples. Functional enrichment analysis showed that RP11-109D20.2 was mainly related to pathways like phosphoric ester hydrolase, oxidoreductase, phosphoric diester hydrolase, and cyclic-nucleotide phosphodiester activities. Moreover, elevated expression of DUOX2 in tumors with high levels of RP11-109D20.2 suggests a link between these genes.

Conclusion: Our data revealed that RP11-109D20.2 may have a considerable role in CRC progression. However, further functional analyses are essential to evaluate the probable role of RP11-109D20.2 as a potential diagnostic marker and its potential role in the dysregulation of cyclic nucleotide phosphodiesterase genes in CRC.

Keywords: Biomarker; Colorectal cancer; Gene expression profiling; Long noncoding RNA RP11-109D20.2; RNA sequencing analysis.

Figure 1

Data preprocessing and quality control of the differential gene expression analysis

Figure 2

DELs between tumor and normal tissues in CRC

Figure 3

Functional enrichment and pathway analysis of differentially expressed genes (DEGs) in PRJEB27536 dataset

Figure 4

Weighted gene co-expression network analysis (WGCNA)

Figure 5

(A) Scatter plot represents a descriptive analysis of the relative expression of RP11-109D20.2 in CRC patients. The black lines indicate the thresholds for over- and under-expression. The range between over- and under-expression shows the cases with normal expression of the lncRNA. Legends show minimum, maximum, and mean log2FC for the lncRNA expression; (B) Dot plot represents the expression of intronic and exonic RP11-109D20.2 in CRC patients (P=0.225).