Circular RNA circ-LDLRAD3 as a biomarker in diagnosis of pancreatic cancer

Yang, Fan; Liu, Dongyan; Guo, Jintao; Ge, Nan; Zhu, Ping; Liu, Xiang; Wang, Sheng; Wang, Guoxin; Sun, Siyu

doi:10.3748/wjg.v23.i47.8345

Cited by 168 publications

(144 citation statements)

References 36 publications

(41 reference statements)

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“…3 Competing endogenous RNAs (ceRNAs) compete with other RNAs for the seed region of shared miRNAs, thus modulating the activity of the miRNAs. 9,10 However, many circRNAs still need to be discovered. [4][5][6] Recently, it has been reported that abundant conserved miRNA response elements (MREs) exist in circRNAs, 7 making circRNAs a hot topic in ceRNA family research.…”

Section: Introductionmentioning

confidence: 99%

Construction of a circRNA‐miRNA‐mRNA network to explore the pathogenesis and treatment of pancreatic ductal adenocarcinoma

Xiao

2019

J of Cellular Biochemistry

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Background Many studies focusing on circular RNAs (circRNAs) have recently been published. However, a large number of circRNAs remain to be explored. This study was designed to discover new circRNAs and investigate their potential roles in the pathogenesis of pancreatic ductal adenocarcinoma (PDAC). Methods A combination of gene chip analysis and bioinformatic methods was utilized to reveal new circRNAs and their possible mechanisms in PDAC. A circRNA‐miRNA‐mRNA network was established based on the results of differential analyses and interaction predictions. Promising drugs for treating PDAC were determined by connectivity map (CMap) analysis. Results Expression profile data were collected from the Gene Expression Omnibus database, and integration of differentially expressed circRNAs (DECs) from two gene chips using the RobustRankAggreg method revealed 10 DECs. The microRNA (miRNA) response elements of these 10 DECs were predicted. The predicted miRNAs and differentially expressed miRNAs were intersected, and 12 overlapping miRNAs were acquired. Next, 2908 miRNA target mRNAs and 1187 differentially expressed genes (DEGs) in PDAC were identified and combined, revealing 118 overlapping mRNAs. A protein‐protein interaction network was constructed with the 118 mRNAs, and four hub genes (CDH1, SERPINE1, IRS1 and FYN) were identified. Using Gene Expression Profiling Interactive Analysis, survival analyses were conducted for the four hub genes, and SERPINE1 and FYN were found to be significantly associated with PDAC patient survival. Functional enrichment analysis indicated that these four hub genes are closely associated with certain cancer‐related biological functions and pathways. In addition, CMap analysis based on the four hub genes was performed to screen potential therapeutic agents for PDAC, and three bioactive chemicals (celastrol, 5109870 and MG‐132) were discovered. Conclusions The results of this study further our understanding of the pathogenesis and treatment of PDAC from the perspective of the circRNA‐related competing endogenous RNA network.

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Section: Introductionmentioning

confidence: 99%

Construction of a circRNA‐miRNA‐mRNA network to explore the pathogenesis and treatment of pancreatic ductal adenocarcinoma

Xiao

2019

J of Cellular Biochemistry

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“…As was discovered by Yang et al, circLDLRAD3 was upregulated and was significantly associated with cell invasion and metastasis in PC [13]. Chen et al studied the circrna_100782 regulation through the IL6-STAT3 pathway on PC cell proliferation [14].…”

Section: Discussionmentioning

confidence: 96%

circZMYM2 Competed Endogenously with miR-335-5p to Regulate JMJD2C in Pancreatic Cancer

Cai

Zhang

et al. 2018

Cell Physiol Biochem

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Background/Aims: We aimed to study the involvement of circZMYM2 (hsa_circ_0099999) in pancreatic cancer (PC) cell proliferation, apoptosis and invasion and to figured out the underlying mechanism of circZMYM2 regulating miR-335-5p and JMJD2C. Methods: CircRNA differential expressions in twenty PC samples and paired normal tissue samples were analyzed using Arraystar Human CircRNA microarray V1. CircZMYM2 expression level was determined via qRT-PCR. The effects of circZMYM2 inhibition and overexpression on cell proliferation, cell apoptosis and cell invasion were investigated by CCK-8 assays, Flow cytometry assays and Transwell assays. An animal experiment on nude mice was put forward to test the influence of circZMYM2 knockdown on tumor growth. The relationship between circZMYM2, miR-335 and JMJD2C was verified by RNA pull down, dual-luciferase reporter assays and rescue experiment. The effect of circZMYM2 and miR-335-5p on the expression of JMJD2C protein was detected by western blot. Results: CircZMYM2 overexpression was observed in both PC tissues and cells. Knockdown of circZMYM2 inhibited proliferation, induced apoptosis, and weakened invasion ability of cancer cells. Tumor growth was restrained in vivo. CircZMYM2 repressed the expression of its target miR-335-5p. MiR-335-5p attenuated pancreatic cancer development via inhibition of JMJD2C. Conclusion: Our study demonstrated that circZMYM2 promoted PC progression. CircZMYM2 had a sponge effect on miR-335-5p and modulated the downstream oncogene JMJD2C.

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“…Among the included publications, a total of 43 articles on 64 studies were analyzed involving 10,123 subjects in Table . Of the 64 studies, five studies focused on colorectal cancer (Ji et al, ; Wang, Li, et al, ; Wang et al, ; Zhang, Yang, et al, ; Zhuo, Lin, Chen, Huang, & Hu, ), 10 on breast cancer (Lu et al, ; Yin et al, ), 22 on gastric cancer (Chen, Li, Zhao, Xiao, & Guo, ; Huang, He, Liang, Huang, & Zhu, ; Li, et al, , ; Li, Shao, et al, ; Li, Song, et al, ; Lu et al, ; Lu, Shao, Ye, Xiao, & Guo, ; Shao, Chen, et al, ; Shao, Li, et al, ; Shao, Yang, et al, ; Sun, Tang, et al, ; Tian, Chen, Li, & Xiao, ; Wei et al, ; Xie et al, ; Zhao, Chen, Li, Xiao, & Zhang, ), four on lung cancer (Li, Wang, Chen, Chen, & Jin, ; Zhu et al, ; Zong et al, ), 16 on hepatocellular carcinoma (Chen, Zhang, Lin, Song, & Wang, ; Fu et al, , ; Li et al, ; Qin et al, ; Shang et al, ; Yao et al, ; Yao et al, ; Zhang, Zhang, Lin, & Wang, ; Zhang, Zhou, et al, ; Zhang, Xu, et al, ) and seven on other cancers (Fan, Cao, Liu, Zhang, & Li, ; Lan et al, ; Li et al, ; Sun, Li, et al, ; Teng et al, ; Wang, Xue, et al, ; Yang et al, ). Moreover, three articles with 13 studies explored the diagnostic value of the combined circRNAs (Chen, Li, Zhao, et al, ; Fan et al, ; Li, Shao, et al, ) in Table .…”

Section: Resultsmentioning

confidence: 99%

“…Multiple studies found that single circRNAs yield good diagnostic performance in tissue or plasma (Shang et al, ; Sun, Tang, et al, ; Wang, Li, et al, ; Zong et al, ). Moreover, several studies provided that single circRNAs in combination with other plasma protein biomarkers such as CEA, CA‐15.3, CA‐125 and AFP possess better diagnostic performance (Huang et al, ; Prefumo, ; Yang et al, ; Yin et al, ; Zhang, Yang, et al, ). Additionally, a single circRNA combined with other circRNAs obtained also had better diagnostic accuracy (Li, Chen, et al, ; Li, Shao, et al, ; Ren & Xin, ).…”

Section: Discussionmentioning

confidence: 99%

Diagnostic performance of circular RNAs in human cancers: A systematic review and meta‐analysis

et al. 2019

Molec Gen & Gen Med

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Background Recently, accumulating evidence have revealed that circular RNA (circRNA) was deregulated in multiple types of cancer, suggesting that circRNA might serve as a novel candidate biomarker of cancer diagnosis. However, inconsistent results have become an obstacle in applying circRNAs to clinical practice. The aim of this study is to evaluate diagnostic value of circRNAs among cancers. Methods A literature search was systematically performed among PubMed, Sciencedirect, Cochrane Library, Web of Science, Wanfang, and Chinese National Knowledge Infrastructure databases up to February 15, 2019. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratios, negative likelihood ratios, diagnostic odds ratio, and area under the SROC curve (AUC) were applied to evaluate diagnostic performance of circRNAs. Results In total, the study included 64 studies with single circRNA and 13 studies with combined circRNAs. Overall, the study presented that a single circRNA had moderate diagnostic value, with a SEN of 0.75, a SPE of 0.76, and an AUC of 0.82. The plasma circRNAs had higher diagnostic accuracy than tissue (AUC: 0.87, 95% confidence interval [CI]: 0.83–0.89 for plasma/serum subgroup; AUC: 0.79, 95% CI: 0.75–0.82 for tissue subgroup). Furthermore, the combined circRNAs had good diagnostic efficacy for GC, with a SEN of 0.89, a SPE of 0.94, and an AUC of 0.97, respectively. Conclusion This study confirmed that circRNAs may be candidate biomarkers for cancer diagnosis. In particular, diagnosis of combined circRNAs will be a new alternative applied to clinical research and practice for cancer.

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Circular RNA circ-LDLRAD3 as a biomarker in diagnosis of pancreatic cancer

Cited by 168 publications

References 36 publications

Construction of a circRNA‐miRNA‐mRNA network to explore the pathogenesis and treatment of pancreatic ductal adenocarcinoma

Construction of a circRNA‐miRNA‐mRNA network to explore the pathogenesis and treatment of pancreatic ductal adenocarcinoma

circZMYM2 Competed Endogenously with miR-335-5p to Regulate JMJD2C in Pancreatic Cancer

Diagnostic performance of circular RNAs in human cancers: A systematic review and meta‐analysis

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