Hsa_circ_0000467 promotes cancer progression and serves as a diagnostic and prognostic biomarker for gastric cancer

Abstract

Background Emerging evidence indicates that dysregulation of circular RNAs (circRNAs) is implicated in the development of malignancies. However, the diagnostic value and functional role of circRNAs in gastric cancer (GC) remain largely elusive. Methods Quantitative reverse transcription‐polymerase chain reaction (qRT‐PCR) was performed to detect the expression of hsa_circ_0000467 in tissues, cell lines, and plasma. A receiver operating characteristic (ROC) curve was constructed to estimate the diagnostic value of hsa_circ_0000467. The association between the expression level of hsa_circ_0000467 and the clinicopathological features was analyzed. Moreover, cell functional assays were performed. Results Hsa_circ_0000467 was significantly upregulated in GC tissue compared to adjacent nontumor tissue (n = 51, P < 0.05). Similar results were detected in the HGC‐27, MGC‐803, AGS, NUGC‐3, GES‐1 cell lines (n = 15, P < 0.001), and in the plasma samples from GC patients (n = 20, P < 0.05). The area under the ROC curve of hsa_circ_0000467 was 0.790, which is superior to commonly used biomarkers including CEA and CA‐724. We found that the expression levels of hsa_circ_0000467 in the same patient were significantly lower after surgery (n = 20, P < 0.05). Moreover, the hsa_circ_0000467 expression level is closely associated with TNM stage. Additionally, Cox multivariate analysis showed that hsa_circ_0000467 is a novel independent prognostic factor. Furthermore, in vitro experiments demonstrated that knockdown of hsa_circ_0000467 markedly inhibited the proliferation, migration, and invasion of GC cells. Moreover, hsa_circ_0000467 silencing increased tumor apoptosis in vitro. Conclusion Hsa_circ_0000467 can act as a novel noninvasive biomarker for the diagnosis and prognosis of GC and may be a potential therapeutic target for GC.

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

“…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 .…”

“…Among the included publications, a total of 43 articles on 64 studies were analyzed involving 10,123 subjects in Table S1. Of the 64 studies, five studies focused on colorectal cancer (Ji et al, 2018;Wang, Li, et al, 2018;Wang et al, 2015;Zhang, Yang, et al, 2018;Zhuo, Lin, Chen, Huang, & Hu, 2017), 10 on breast cancer Yin et al, 2018), 22 on gastric cancer (Chen, Li, Zhao, Xiao, & Guo, 2017;Huang, He, Liang, Huang, & Zhu, 2017;Li, Shao, et al, 2018;Li, Song, et al, 2017;Lu et al, 2018;Shao, Chen, et al, 2017;Shao, Li, et al, 2017;Sun, Tang, et al, 2018;Tian, Chen, Li, & Xiao, 2018;Wei et al, 2019;Xie et al, 2018;Zhao, Chen, Li, Xiao, & Zhang, F I G U R E 1 The flow diagram of this meta-analysis 2018), four on lung cancer (Li, Wang, Chen, Chen, & Jin, 2018;Zhu et al, 2017;Zong et al, 2018), 16 on hepatocellular carcinoma (Chen, Zhang, Lin, Song, & Wang, 2018;Fu et al, 2018Fu et al, , 2017Li et al, 2019;Qin et al, 2016;Shang et al, 2016;Yao et al, 2017;Yao et al, 2018;Zhang, Zhou, et al, 2018; and seven on other cancers (Fan, Cao, Liu, Zhang, & Li, 2019;Lan et al, 2018;Li et al, 2019;Sun, Li, et al, 2018;…”

Gastric juice piR‐1245: A promising prognostic biomarker for gastric cancer

“…The detection of piRNA-1245 in GJ could be a new avenue for differentiating GC from healthy people. [24][25][26][27][28][29] Some altered ncRNAs played a crucial role in the regulation of malignant phenotypes of tumor. 24 Mo et al elucidated that lncRNA RP11-555H23.1 showed an important role in the occurrence of GC, and used as a new marker of GC.…”

Reduced expression of circRNA hsa_circ_0067582 in human gastric cancer and its potential diagnostic values

“…On a global scale, a recent study showed that the 5‐year survival rate of stage I patients can be more than 90%, while that of the stage IV patients who already show distant metastases is only approximately 18% . Yet, traditional serum tumor biomarkers such as carcinoembryonic antigen (CEA), carbohydrate antigen 19‐9(CA19‐9), and carbohydrate antigen 72‐4 (CA72‐4) are not very effective in the diagnosis of GC . Their sensitivity and specificity are relatively low .…”

“…5,6 Yet, traditional serum tumor biomarkers such as carcinoembryonic antigen (CEA), carbohydrate antigen 19-9(CA19-9), and carbohydrate antigen 72-4 (CA72-4) are not very effective in the diagnosis of GC. 7,8 Their sensitivity and specificity are relatively low. 9 Therefore, it is necessary to search for stable, non-invasive, and cost-effective biomarkers to improve the diagnosis and monitoring patients with GC.…”