High-throughput sequencing of circRNAs reveals novel insights into mechanisms of nigericin in pancreatic cancer

Abstract

Background: Our previous study had proved that nigericin could reduce colorectal cancer cell proliferation in dose- and time-dependent manners by targeting Wnt/β-catenin signaling. To better elucidate its potential anti-cancer mechanism, two pancreatic cancer (PC) cell lines were exposed to increasing concentrations of nigericin for different time periods, and the high-throughput sequencing was performed to explore the circRNA expression profiles after nigericin exposure on pancreatic cancer (PC) cells.

Results: In this study, a total of 183 common differentially expressed circRNAs were identified, and the reliability and validity of the sequencing data were verified by the PCR analysis. According to the parental genes of circRNAs, the GO analysis was performed to predict the most enriched terms in the biological process, cellular components and molecular functions. The KEGG analysis and pathway-pathway network exhibited the potential signal pathways and their regulatory relationships. Meanwhile, a potential competing endogenous RNA (ceRNA) mechanism through a circRNA-miRNA-mRNA network was applied to annotate potential functions of these common differentially expressed circRNAs, and these predicted miRNAs or mRNAs might be involved in nigericin damage.

Conclusions: By the bioinformatics method, our data will facilitate the understanding of nigericin in PC cells, and provide new insight into the molecular mechanism of nigericin toward cancer cells. This is the first report that discusses the potential functions of nigericin in cancers through the bioinformatics method. Our data will facilitate the understanding of nigericin-mediated anti-cancer mechanisms in PC.

Keywords: CircRNAs; High-throughput sequencing; Mechanism; Nigericin; Pancreatic cancer.

Fig. 1

Sensitivity of human PC cells to nigericin. a, b PANC-1 and SW1990 cells were exposed to increasing concentrations of nigericin for different time periods (0, 8, 16 or 32 h), and nigericin treatment significantly reduced the cell viability in a concentration-dependent manner. c, d The IC50 values of nigericin in PANC-1 and SW1990 cells at different time points (8, 16 and 32 h) were calculated and compared. Nigericin inhibited the cell viabilities time dependently. (*P < 0.05)

Fig. 2

The common differentially expressed circRNAs during nigericin treatment were indentified. a The venn analysis among the three comparison groups showed that 183 common differentially expressed circRNAs (141 up-regulated and 42 down-regulated ones) were involved in the nigericin treatment. b The cluster heat map of these common differentially expressed circRNAs was presented

Fig. 3

The characterizations of the common differentially expressed circRNAs. a Analyzing these 183 circRNAs, 159 ones were sense-overlapping, 22 ones were derived from exons, and only 2 circRNAs were intergenic. b The distribution of the common differentially expressed circRNAs on the human chromosomes was depicted

Fig. 4

Validation for the sequencing data by qRT-PCR. a The expressions of 5 randomly up-regulated circRNAs after 32 h-nigericin exposure were detected by qRT-PCR, compared to the 0 h-nigericin treatment. b The expressions of 5 randomly down-regulated circRNAs after 32 h-nigericin exposure were also detected by qRT-PCR. (*P < 0.05)

Fig. 5

The GO and KEGG analysis were performed by analyzing 164 parental genes of the 183 common differentially expressed circRNAs. a A total of 164 parental genes were obtained from the 183 common differentially expressed circRNAs, and the GO analysis presented the top 10 enriched GO terms in the biological process, cellular components and molecular functions. b The KEGG pathway analysis exhibited the top 20 most enrichment pathways