Background
Emerging studies have proved that colonic inflammation caused by refractory inflammatory bowel disease (IBD) can initiate the colitis‐associated cancer (CAC), but the transition from inflammation to carcinoma is still largely unknown.
Methods
In this study, mouse colitis and CAC models were established, and the RNA‐seq by circRNA microarray was employed to identify the differentially expressed circRNAs and mRNAs in different comparisons (DSS vs. NC and AOM/DSS vs. DSS). The bioinformatics analyses were used to search the common characteristics in mouse colitis and CAC.
Results
The K‐means clustering algorithm packaged these differential expressed circRNAs into subgroup analysis, and the data strongly implied that mmu_circ_0001109 closely correlated to the pro‐inflammatory signals, while mmu_circ_0001845 was significantly associated with the Wnt signalling pathway. Our subsequent data in vivo and in vitro confirmed that mmu_circ_0001109 could exacerbate the colitis by up‐regulating the Jak‐STAT3 and NF‐kappa B signalling pathways, and mmu_circ_0001845 promoted the CAC transformation through the Wnt signalling pathway. By RNA blasting between mice and humans, the human RTEL1‐ and PRKAR2A‐derived circRNAs, which might be considered as homeotic circRNAs of mmu_circ_0001109 and mmu_circ_0001845, respectively, were identified. The clinical data revealed that RTEL1‐derived circRNAs had no clinical significance in human IBD and CAC. However, three PRKAR2A‐derived circRNAs, which had the high RNA similarities to mmu_circ_0001845, were remarkably up‐regulated in CAC tissue samples and promoted the transition from colitis to CAC.
Conclusions
Our results suggested that these human PRKAR2A‐derived circRNAs could be novel candidates for distinguishing CAC patients and predicted the prognosis of CAC.
Objectives: Nigericin, an antibiotic derived from Streptomyces hygroscopicus, has been proved to exhibit promising anti-cancer effects on a variety of cancers. Our previous study investigated the potential anti-cancer properties in pancreatic cancer (PC), and demonstrated that nigericin could inhibit the cell viabilities in concentration-and time-dependent manners via differentially expressed circular RNAs (circRNAs). However, the knowledge of nigericin associated with long non-coding RNA (lncRNA) and mRNA in pancreatic cancer (PC) has not been studied. This study is to elucidate the underlying mechanism from the perspective of lncRNA and mRNA. Methods: The continuously varying molecules (lncRNAs and mRNAs) were comprehensively screened by high-throughput RNA sequencing. Results: Our data showed that 76 lncRNAs and 172 mRNAs were common differentially expressed in the nigericin anti-cancer process. Subsequently, the bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, coding and non-coding co-expression network, cis-and trans-regulation predictions and protein-protein interaction (PPI) network, were applied to annotate the potential regulatory mechanisms among these coding and non-coding RNAs during the nigericin anti-cancer process. Conclusions: These findings provided new insight into the molecular mechanism of nigericin toward cancer cells, and suggested a possible clinical application in PC.
Background Nigericin, an antibiotic derived from Streptomyces hygroscopicus, has been proved to exhibit promising anti-cancer effects on a variety of cancers. Our previous study investigated the potential anti-cancer properties in pancreatic cancer (PC), and demonstrated that nigericin could inhibited the cell viabilities in concentration- and time-dependent manners via differentially expressed circular RNAs (circRNAs). However, the knowledge of nigericin associated with long non-coding RNA (lncRNA) and mRNA in pancreatic cancer (PC) has not been studied. This study is to elucidate the underlying mechanism from the perspective of lncRNA and mRNA.Methods The continuously varying molecules (lncRNAs and mRNAs) were comprehensively screened by high-throughput RNA sequencing.Results Our data showed that 76 lncRNAs and 172 mRNAs were common differentially expressed in the nigericin anti-cancer process. Subsequently, the bioinformatics analyses, including GO and KEGG analysis, coding and non-coding co-expression network, cis- and trans-regulation predictions and PPI network, were applied to annotate the potential regulatory mechanisms among these coding and non-coding RNAs during the nigericin anti-cancer process.Conclusion These findings provided new insight into the molecular mechanism of nigericin toward cancer cells, and suggested a possible clinical application in PC.
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