RNA-binding protein CELF6 modulates transcription and splicing levels of genes associated with tumorigenesis in lung cancer A549 cells

Abstract

CELF6 (CUGBP Elav-Like Family Member 6), a canonical RNA binding protein (RBP), plays important roles in post-transcriptional regulation of pre-mRNAs. However, the underlying mechanism of lower expressed CELF6 in lung cancer tissues is still unclear. In this study, we increased CELF6 manually in lung cancer cell line (A549) and utilized transcriptome sequencing (RNA-seq) technology to screen out differentially expressed genes (DEGs) and alternative splicing events (ASEs) after CELF6 over-expression (CELF6-OE). We found that CELF6-OE induced 417 up-regulated and 1,351 down-regulated DEGs. Functional analysis of down-regulated DEGs showed that they were highly enriched in immune/inflammation response- related pathways and cell adhesion molecules (CAMs). We also found that CELF6 inhibited the expression of many immune-related genes, including TNFSF10, CCL5, JUNB, BIRC3, MLKL, PIK3R2, CCL20, STAT1, MYD88, and CFS1, which mainly promote tumorigenesis in lung cancer. The dysregulated DEGs were also validated by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) experiment. In addition, CELF6 regulates the splicing pattern of large number of genes that are enriched in p53 signaling pathway and apoptosis, including TP53 and CD44. In summary, we made an extensive analysis of the transcriptome profile of gene expression and alternative splicing by CELF6-OE, providing a global understanding of the target genes and underlying regulation mechanisms mediated by CELF6 in the pathogenesis and development of lung cancer.

Keywords: Alternative splicing; CELF6; Lung cancer; RNA-Binding Protein; RNA-seq.

Figure 1. Expression pattern and prognosis analysis of CELF6 in multiple tumor and lung cancer samples.

(A) Box plot of CELF6 expression levels (TPM) in 16 tumor types from TCGA database. *p-value < 0.05, unpaired Student’s t-test. The abbreviation of these tumor types could be found from the TCGA database (https://www.cancer.gov). (B) Box plot of CELF6 expression levels (TPM) in another 15 tumor types from TCGA database. *p-value < 0.05, unpaired Student’s t-test. Two lung cancer types were highlighted by red frame. (C) Violin plot showing the expression level change of CELF6 in the four disease stages of LUAD patient samples. Statistical difference was performed by one-way ANOVA method. (D) The Kaplan-Meier plot showing the prognosis difference between LUAD patients with high and low CELF6 expression levels.

Figure 2. High quality sequencing data were obtained for expression and alternative splicing analysis.

(A) The histogram showed the RT-qPCR results of control and CELF6-OE samples. Four biological replicates per sample. ****p < 0.0001, Student’s t-test. (B) The result of western blot experiment showed that the CELF6 overexpression was successful. (C) The expression level of CELF6 was up-regulated after overexpression based on RNA-seq (three biological replicates per sample). Error bars represent mean ± standard error of mean (SEM). *** p < 0.001, Student’s t-test. (D) Principal Component Analysis (PCA) based on FPKM values of all genes showed the sample correlation.

Figure 3. Differential expression analysis revealed that CELF6 downregulates large number of inflammation genes.

(A) The number of differentially expressed genes (DEGs) based on the standard p-value < 0.01 and fold change ≥ 1.5 or ≤ 2/3. Up-regulated genes are labeled in red, whereas down- regulated are labeled in blue in the volcano plot. (B) The expression levels heatmap of all DEGs and reflected the change of genes expression. (C,D) Bar plot exhibited the most enriched KEGG pathways results of the Down-regulated and down-regulated DEGs. (E) Bar plot showing the expression pattern and statistical difference of DEGs. Reverse transcription qPCR validation of DEGs regulated by CELF6 in cancer cells; black bars are for the control group and grey bars for CELF6 overexpression. ***p-value < 0.001; ****p-value < 0.0001.

Figure 4. Identification and functional analysis of CELF6-regulated alternative splicing events in A549 cells.

(A) The bar plot showing the number of all significant regulated alternative splicing events (RASEs). X-axis: RASE number. Y-axis: the different types of AS events. (B) Hierarchical clustering heat map of all significant RASEs based on splicing ratios. (C,D) Bar plot exhibited the most enriched GO biological process and KEGG pathways of the regulated alternative splicing genes (RASGs). (E) Venn diagram shows the result of overlap analysis between CELF6-regulated differentially expressed genes (DEGs) and alternative splicing genes (RASGs).

Figure 5. CELF6 regulated alternative splicing of TP53 and CD44.

CELF6 regulated the alternative splicing event of TP53 (A) and CD44 (B) Left panel: IGV-sashimi plot showing the regulated alternative splicing events and binding sites across mRNA. Reads distribution of RASE is plotted in the up panel and the transcripts of each gene are shown below. Right panel: The schematic diagrams depict the structures of ASEs. RNA-seq validation of ASEs are shown at the bottom of the right panel. Error bars represent mean ± SEM. ****p-value < 0.0001; **p-value < 0.01; *p-value < 0.05; Student’s t-test.