Prognostic and Diagnostic Significance of circRNA Expression in Esophageal Cancer: A Meta-analysis

Lin, Hong; Yuan, Jinpeng; Liang, Guoxi; Wu, Yanxuan; Chen, Liming

doi:https://doi.org/10.1155/2020/8437250

Gastroenterology Research and Practice

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2020 | Article ID 8437250 | https://doi.org/10.1155/2020/8437250

Prognostic and Diagnostic Significance of circRNA Expression in Esophageal Cancer: A Meta-analysis

Hong Lin,^1,2Jinpeng Yuan,^2,3Guoxi Liang,^1,2Yanxuan Wu,^2,4and Liming Chen¹

Academic Editor: Oronzo Brunetti

Received27 Jul 2020

Revised06 Nov 2020

Accepted16 Nov 2020

Published01 Dec 2020

Abstract

Background and Aims. Circular RNA (circRNA) demonstrates potential biological application in various solid tumors. We intended to evaluate the diagnostic, prognostic, and clinicopathological value of circRNA for esophageal cancer (EC). Methods. We screened relative studies from Pubmed, Embase, Web of Science, and Cochrane Library. The diagnostic role of circRNAs was testified by pooled sensitivity and specificity. Pooled odds ratio (OR) and pooled hazard ratio (HR) were computed to appraise the clinicopathological and prognostic value, respectively. Results. There were total 15 articles suitable with our included criteria, in which 7 for diagnosis, 8 for prognosis, and 9 for clinicopathological features. The pooled sensitivity and specificity were 0.77 and 0.80, respectively, while the AUC was 0.85. Patients with aberrant expression of circRNAs had a 2.92-fold increased risk of developing EC. The proportion of EC patients with normal circRNA expression only accounted for 29%. Upregulated expression of oncogenic circRNA was correlated with poor clinicopathological features, including lymph node metastasis, tumor size, and T classification, while downregulation of tumor-suppressor circRNA was contributed to worse TNM stage. As for prognosis, upregulated expression of circRNA carried out a diverse survival outcome, with a pooled HR of 2.76 for tumor promoter and that of 0.21 for tumor suppressor. High expression of oncogenic circRNA in both plasma and tumor tissue would lead to a shorter survival duration. Conclusion. circRNAs might be a promising biomarker for diagnosis, prognosis, and clinicopathological features of EC.

1. Introduction

Circular RNA (circRNA), consisting of a covalently closed circular structure without 5 to 3 polarity, is an endogenous noncoding RNA produced by unconventional splicing of pre-RNAs [1–3]. It was initially discovered by Sanger et al. [4] in 1976; then, it was proved to adsorb endogenous micro-RNAs (miRNAs) as miRNAs sponges in 2013 [5, 6]. Besides, circRNA plays roles in transcription, selective splicing regulation, cell cycle regulation, methylation modification, and information transport [7]. Other studies demonstrated that circRNA accelerated proliferation, differentiation, and apoptosis of tumor cell [8]. With the development of sequencing technology, circRNA was found to be of remarkable importance in various diseases, including cardiovascular disease, diabetes, Alzheimer’s disease, and cancer [5, 7, 9, 10]. Due to its high conservatism and stability, circRNA might become a promising biomarker in cancer diagnosis and therapy.

Esophageal cancer (EC) is a common malignancy of the digestive tract with poor prognosis. In all malignancies, EC ranks among the top ten both in morbidity and mortality [11]. Adenocarcinoma and squamous cell carcinoma are two most frequent histologic types of EC. The former occurs mainly in developed countries, and the latter occurs mostly in Eastern Asia [12, 13]. Regrettably, EC is often diagnosed at middle-advanced stage, which results in the omitting of optimal therapeutic opportunity for patients. The primary reasons include the delayed emergence of initial symptoms, discomfort caused by endoscopy, and the nonspecific and insensitive tumor markers [14]. Recently, the role of epigenetics in esophageal cancer is gradually being discovered. The occurrence and progression of malignant tumors are usually first accompanied by changes in the microenvironment and signaling pathways, such as the regulation of the vascular network of EC by miR-126 and miR-377 [15]. Many studies discovered abnormal expression of circRNA in EC, which may provide crucial reference for diagnosis and treatment. We incorporated relevant studies for a meta-analysis, in order to summarize the correlation between circRNA expression and diagnosis, prognosis, and clinical characteristics of EC.

2. Materials and Methods

2.1. Search Strategy

Our research was carried out on the basis of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) checklist (Supplementary file (available here)) [16]. We searched for studies from four online databases, including Pubmed, Embase, Web of Science, and Cochrane Library, by using the following terms: (1) (“esophageal carcinoma” or “esophageal cancer” or “esophageal tumor” or “esophageal neoplasm” and (2) (“circular RNA” or “circRNA”). The deadline for searching was June 17th, 2020. Two researchers (HL and JPY) evaluated the appropriate studies and extracted the imperative data independently. If there was any disagreement, a third researcher (LMC) together with HL and JPY would discuss and resolve it.

2.2. Study Selection

Studies that met the following eligibility were included into our meta-analysis: (1) patients were diagnosed as EC by positive histology, (2) the studies were performed to estimate the diagnostic or prognostic efficiency of circRNA for EC or to identify the relationship between the expression of circRNA and clinicopathologic features, and (3) cohort or case-control researches. The excluded criteria were listed as the following: (1) articles that were not published in English; (2) review, meta-analysis, letter, and animal studies; and (3) with incomplete information.

2.3. Data Extraction and Quality Assessment

Two researchers (HL and JPY) extracted the following information from each study independently: (1) first author, country, edition year, cancer and circRNA type, the number of samples, sample species, experimental method, and regulated signature of circRNA; (2) the follow-up duration of EC patients; (3) diagnostic specificity and sensitivity, the area under the receiver operating characteristic (ROC) curve (AUC), the value of true positive (TP), false negative (FN), true negative (TN), and false positive (FP); and (4) clinicopathological features including age, gender, smoking, drinking, TNM stage, T classification, lymph node metastasis, distant metastasis, tumor size, and differentiation. If the parameter of TP, TN, FP, and FN was not offered, we assessed it according to sample size, specificity, sensitivity, and AUC.

Two independent researchers (HL and JPY) performed quality assessment of the included studies by using the Newcastle-Ottawa Scale (NOS) [17]. A score no less than 6 was conferred with high quality for a study.

2.4. Statistical Analysis

Stata 15.0 was utilized to develop related statistical analysis. By combining the number of TP, TN, FP, and FN, the pooled specificity, sensitivity, diagnostic odds ratio (DOR), and negative and positive likelihood ratio (NLR and PLR) were calculated. Summary receiver operator characteristic (sROC) curve with AUC (the area under sROC) was plotted to evaluate the diagnostic value of circRNA. Pooled odds ratios (ORs) with 95% confidence intervals (CI) were utilized to assess the relationship between the expression of circRNA and clinicopathologic features. In addition, we estimated the prognostic value of circRNA for overall survival (OS) via using pooled hazard ratios (HRs). Subgroup analysis was performed to determine whether the aberrant expression of circRNA in plasma or tumor tissue had an impact on prognosis. ² value and chi-squared test were used to evaluate heterogeneity. A <50% ² value or a <0.10 value was considered of no conspicuous heterogeneity, so a fixed-effect model was applicable. Otherwise, a random-effect model should be adopted [18]. Potential source of heterogeneity was investigated via sensitivity analyses. In addition, funnel plots and Begg and Egger’s tests were established to estimate publication bias.

3. Results

3.1. Search Results

The flowchart of study selection was plotted in Figure 1. A total of 242 articles were retrieved from online databases, in which 15 were suitable for being incorporated in the meta-analysis. There were seven [19–25] and eight [19–21, 23, 24, 26–28] articles on diagnostic accuracy and prognostic evaluation, respectively, while nine [20, 26–33] articles on clinicopathological parameter. Notably, Fan et al. found that both has_circ_0001946 and has_circ_0062459 were associated with the diagnosis of EC in their research. As a result, 8 datasets from 7 articles were adopted in analysis of diagnosis.

3.2. Study Characteristics and Quality Assessment

Tables 1 and 2 show us the basic characteristics of the included researches. A total of 16 kinds of circRNA, and 1032 participants were included. The individuals in each study ranged from 26 to 210. All studies were published from 2018 to 2020. The follow-up duration was from 20 to 90 months. Table 1 shows the 8 datasets with sensitivity, specificity, and AUC. As Table 2 listed, 7 kinds of circRNA upregulated (tumor promoters) in EC, and 1 downregulated (tumor suppressors). The expression of circRNA was calibrated by quantitative real-time reverse transcription PCR (qRT-PCR). The sample specie for exploring diagnostic value of circRNA was plasma, while that for exploring clinicopathological features was tumor tissue. As for prognostic analysis, species included both plasma and tumor sample. What is more, the involved studies were of high quality (Table 3).

3.3. Diagnosis Analysis

There were 8 datasets from 7 articles finally incorporated into this meta-analysis. The forest plot demonstrated the pooled sensitivity and specificity of circRNA (Figure 2). Because of observable heterogeneity ( and ), a random-effect model was utilized. The calculated results revealed a pooled specificity of 0.80 (95% CI: 0.69–0.88) and a pooled sensitivity of 0.77 (95% CI: 0.69–0.83). The pooled AUC was 0.85 (95% CI: 0.82-0.88) (Figure 3). The conclusive DOR was 13.71 (95% CI 8.06-23.32) (Figure 4). Moreover, the pooled PLR was 3.92 (95% CI 2.51-6.12), and pooled DLR was 0.29 (95% CI 0.22-0.37) (Figure 5). Aforementioned outcomes demonstrated that circRNA could be a precise biomarker for EC diagnosis.

3.4. Clinical Parameters

Table 4 reveals the relation between clinicopathological features and circRNA. High expression of tumor-promoter circRNA was contributed to poor clinicopathological features (tumor size: OR 1.680, 95% CI 1.031, 2.738; T staging: OR 1.729, 95% CI 1.074, 2.785; metastasis of lymph nodes: OR 4.657, 95% CI 1.951, 11.112). Furthermore, low expression of tumor-suppressor circRNA implied worse TNM staging (OR 2.891, 95% CI 1.052, 7.949). Of important, there was no significant difference between the expression of circRNA and other clinicopathologic parameters, including age, gender, differentiation, and distant metastasis.

3.5. Overall Survival (OS)

With no significant heterogeneity (), fixed-effect models were applied to estimate the role of circRNA in OS prognosis. Upregulated tumor-promoter circRNA was correlated with worse OS (HR 2.76, 95% CI 2.09-3.63, Figure 6(a)) for EC patients. Oppositely, upregulation of tumor-suppressor circRNA notably carried out more favorable OS probability (HR 0.21, 95% CI 0.08-0.57, Figure 6(b)). Furthermore, for tumor-promoter circRNA, subgroup analysis declared that the high expression both in plasma (HR 2.52, 95% CI 1.56-4.09) and tissue (HR 2.88, 95% CI 2.06-4.02) carried out worse prognosis (Figure 7).

(a)

(b)

3.6. Publication Bias and Sensitivity Analysis

The funnel plot presented in Figure 8 demonstrated that there was no publication bias in our meta-analysis. We also performed further qualitative analysis by using Begg’s test and Egger’s test to evaluate the publication bias, and the results supported the conclusion that there was no publication bias (Begg’s test: ; Egger’s test: ; Figures 9 and 10). Additionally, sensitivity analysis showed that the outcomes of meta-analysis were invariable when removed the studies one by one, which concluded that the pooled outcomes were stable (Figure 11). What is more, no evidence of publication bias was implied by developing Deeks’ funnel plot asymmetry test (; Figure 12).

4. Discussion

circRNA might be a novel tumor biomarker. Its predictive value in diagnosis and prognosis for malignancy has been gradually explored. Several circRNAs have been certified to be associated with the development and progression of various tumors, such as ciRs-7 [34]. The predictive role of circRNA in different malignancies, including lung cancer, colorectal cancer, and laryngeal cancer, has also been reported recently [35–37]. Niu et al. [38] conducted a meta-analysis to investigate the diagnostic role of circRNA in EC, which illustrated that circRNA had a favorable biological value for EC diagnosis. However, the number of studies included was small, and the relation between circRNA expression and prognosis or clinicopathological characteristics was not investigated. To our knowledge, this is the first meta-analysis involving the relationship between circRNA expression and diagnosis, prognosis, and clinicopathological characteristics of EC. In our analysis, sensitivity and specificity of circRNA for diagnosis were 0.77 and 0.80, respectively, and the AUC was 0.85. In addition, the overall DOR was 13.71, while incorporated PLR and NLR were 3.92 and 0.29, respectively. In other words, patients with the aberrant expression of circRNA were 3.92 times more likely to develop EC compared with the general population, and the proportion of patients with the normal circRNA expression only accounted for 29%. Upregulation of oncogenic circRNA was obviously associated with lymph node metastasis, tumor size, and T classification. Upregulation of downregulation of tumor-suppressor circRNA contributed to poor TNM stage. As for prognostic value, the abnormal expression of circRNA was closely associated with poor OS. Of course, just as the downregulation of miR-20b, miR-27a, and miR-181a leads to the upregulation of drug-resistant genes in gastric cancer to affect the sensitive of chemotherapy, we also expect circRNA to serve for the precise and individualized treatment of EC [39]. This is an attractive challenge that requires more clinical trials.

We investigated the diagnostic value of circRNA for EC. Due to the anomalous expression of circRNA in plasma, it is easy to obtain samples for testing when a person was suspected of suffering from EC. Meanwhile, stable structures and conservative sequences guarantee that circRNA is not prone to denature. The expression of circRNA from preoperative plasma or postoperative tumor tissue is a powerful supplement to the assessment of patient’s prognosis. Our meta-analysis comprised 15 studies involving 1032 patients, which strongly manifested the function of circRNA in diagnosis, prognosis, and clinicopathological relevance for EC. It is expected that more investigations will be performed to further confirm our results, especially on tumor-suppressor circRNA.

Our analysis was developed based on PRISMA guidelines strictly and was accomplished by independent researchers utilizing appropriate retrieval strategies. We screened the studies in compliance with the rigorous inclusion and exclusion criteria. For statistical analyses, we applied precise and appropriate statistical methods, and the statistical outcomes were analyzed and interpreted carefully. Nevertheless, there were still some limitations in our study. First, the number of studies included was relatively small, especially the studies on tumor-suppressor circRNA. In order to further ascertain the results, more studies are necessary to perform in the future. Second, all studies were from China, indicating that studies on other races were needed. In addition, some studies did not provide clear sensitivity, specificity, or HR. We extracted indispensable data from supplied ROC curves and KM curves, which may lead to potential bias. Finally, we analyzed the prognostic role of circRNA by using HR, which was provided in each research via univariate analysis. The tests performed may be statistically significant but biologically less relevant if placed into a more complex context. As a result, an HR obtained from multivariate will be more credible. The prognostic role of circRNA after adjusting for other prognostic factors remains to be further explored.

5. Conclusion

In summary, our meta-analysis declared that the expression of circRNA in plasma had a certain value in the differential diagnosis of EC. Meanwhile, the aberrant expression of circRNA both in malignancy tissue and plasma indicated worse prognosis. circRNA might be a promising biomarker, and further researches are needed to verify its role in EC.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that they have no conflict of interest.

Authors’ Contributions

Hong Lin and Jinpeng Yuan contributed equally to this work.

Acknowledgments

We thank the authors of all the included studies.

Supplementary Materials

The authors have completed the PRIMSA reporting checklist. (Supplementary Materials)

References

L. L. Chen and L. Yang, “Regulation of circRNA biogenesis,” RNA Biology, vol. 12, no. 4, pp. 381–388, 2015.
View at: Publisher Site | Google Scholar
T. B. Hansen, T. I. Jensen, B. H. Clausen et al., “Natural RNA circles function as efficient microRNA sponges,” Nature, vol. 495, no. 7441, pp. 384–388, 2013.
View at: Publisher Site | Google Scholar
C. X. Liu, X. Li, F. Nan et al., “Structure and degradation of circular RNAs regulate PKR activation in innate immunity,” Cell, vol. 177, no. 4, pp. 865–880.e21, 2019.
View at: Publisher Site | Google Scholar
H. L. Sanger, G. Klotz, D. Riesner, H. J. Gross, and A. K. Kleinschmidt, “Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures,” Proceedings of the National Academy of Sciences of the United States of America, vol. 73, no. 11, pp. 3852–3856, 1976.
View at: Publisher Site | Google Scholar
T. B. Hansen, J. Kjems, and C. K. Damgaard, “Circular RNA and miR-7 in cancer,” Cancer Research, vol. 73, no. 18, pp. 5609–5612, 2013.
View at: Publisher Site | Google Scholar
S. Memczak, M. Jens, A. Elefsinioti et al., “Circular RNAs are a large class of animal RNAs with regulatory potency,” Nature, vol. 495, no. 7441, pp. 333–338, 2013.
View at: Publisher Site | Google Scholar
J. Wu, X. Qi, L. Liu et al., “Emerging epigenetic regulation of circular RNAs in human cancer,” Molecular Therapy--Nucleic Acids, vol. 16, pp. 589–596, 2019.
View at: Publisher Site | Google Scholar
Y. Zhong, Y. Du, X. Yang et al., “Circular RNAs function as ceRNAs to regulate and control human cancer progression,” Molecular Cancer, vol. 17, no. 1, p. 79, 2018.
View at: Publisher Site | Google Scholar
Y. Zhao, P. N. Alexandrov, V. Jaber, and W. J. Lukiw, “Deficiency in the ubiquitin conjugating enzyme UBE2A in Alzheimer’s disease (AD) is linked to deficits in a natural circular miRNA-7 sponge (circRNA; ciRS-7),” Genes, vol. 7, no. 12, p. 116, 2016.
View at: Publisher Site | Google Scholar
K. Zhu, X. Hu, H. Chen et al., “Downregulation of circRNA DMNT3B contributes to diabetic retinal vascular dysfunction through targeting miR-20b-5p and BAMBI,” eBioMedicine, vol. 49, pp. 341–353, 2019.
View at: Publisher Site | Google Scholar
F. Bray, J. Ferlay, I. Soerjomataram, R. L. Siegel, L. A. Torre, and A. Jemal, “Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA: A Cancer Journal for Clinicians, vol. 68, no. 6, pp. 394–424, 2018.
View at: Publisher Site | Google Scholar
M. Arnold, I. Soerjomataram, J. Ferlay, and D. Forman, “Global incidence of oesophageal cancer by histological subtype in 2012,” Gut, vol. 64, no. 3, pp. 381–387, 2015.
View at: Publisher Site | Google Scholar
L. A. Torre, F. Bray, R. L. Siegel, J. Ferlay, J. Lortet-Tieulent, and A. Jemal, “Global cancer statistics, 2012,” CA: A Cancer Journal for Clinicians, vol. 65, no. 2, pp. 87–108, 2015.
View at: Publisher Site | Google Scholar
R. L. Siegel, K. D. Miller, and A. Jemal, “Cancer statistics, 2017,” CA: A Cancer Journal for Clinicians, vol. 67, no. 1, pp. 7–30, 2017.
View at: Publisher Site | Google Scholar
P. Leone, A. Buonavoglia, R. Fasano et al., “Insights into the regulation of tumor angiogenesis by micro-RNAs,” Journal of Clinical Medicine, vol. 8, no. 12, p. 2030, 2019.
View at: Publisher Site | Google Scholar
D. Moher, L. Shamseer, M. Clarke et al., “Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement,” Systematic Reviews, vol. 4, no. 1, p. 1, 2015.
View at: Publisher Site | Google Scholar
A. Stang, “Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses,” European Journal of Epidemiology, vol. 25, no. 9, pp. 603–605, 2010.
View at: Publisher Site | Google Scholar
M. Egger, G. Davey Smith, M. Schneider, and C. Minder, “Bias in meta-analysis detected by a simple, graphical test,” BMJ, vol. 315, no. 7109, pp. 629–634, 1997.
View at: Publisher Site | Google Scholar
L. Fan, Q. Cao, J. Liu, J. Zhang, and B. Li, “Circular RNA profiling and its potential for esophageal squamous cell cancer diagnosis and prognosis,” Molecular Cancer, vol. 18, no. 1, p. 16, 2019.
View at: Publisher Site | Google Scholar
X. Hu, D. Wu, X. He et al., “circGSK3β promotes metastasis in esophageal squamous cell carcinoma by augmenting β-catenin signaling,” Molecular Cancer, vol. 18, no. 1, p. 160, 2019.
View at: Publisher Site | Google Scholar
E. Huang, J. Fu, Q. Yu et al., “CircRNA hsa_circ_0004771 promotes esophageal squamous cell cancer progression via miR-339-5p/CDC25A axis,” Epigenomics, vol. 12, no. 7, pp. 587–603, 2020.
View at: Publisher Site | Google Scholar
J. Rong, Q. Wang, Y. Zhang et al., “Circ-DLG1 promotes the proliferation of esophageal squamous cell carcinoma,” Oncotargets and Therapy, vol. Volume 11, pp. 6723–6730, 2018.
View at: Publisher Site | Google Scholar
Q. Wang, H. Liu, Z. Liu et al., “Circ-SLC7A5, a potential prognostic circulating biomarker for detection of ESCC,” Cancer Genetics, vol. 240, pp. 33–39, 2020.
View at: Publisher Site | Google Scholar
Q. Wang, Q. Zhang, H. Sun et al., “Circ-TTC17 promotes proliferation and migration of esophageal squamous cell carcinoma,” Digestive Diseases and Sciences, vol. 64, no. 3, pp. 751–758, 2019.
View at: Publisher Site | Google Scholar
Y. Zhang, Q. Wang, D. Zhu, J. Rong, W. Shi, and X. Cao, “Up-regulation of circ-SMAD7 inhibits tumor proliferation and migration in esophageal squamous cell carcinoma,” Biomedicine & Pharmacotherapy, vol. 111, pp. 596–601, 2019.
View at: Publisher Site | Google Scholar
S. Cao, G. Chen, L. Yan, L. Li, and X. Huang, “Contribution of dysregulated circRNA_100876 to proliferation and metastasis of esophageal squamous cell carcinoma,” Oncotargets and Therapy, vol. Volume 11, pp. 7385–7394, 2018.
View at: Publisher Site | Google Scholar
R. C. Li, S. Ke, F. K. Meng et al., “CiRS-7 promotes growth and metastasis of esophageal squamous cell carcinoma via regulation of miR-7/HOXB13,” Cell Death & Disease, vol. 9, no. 8, p. 838, 2018.
View at: Publisher Site | Google Scholar
Z. H. Pan, J. T. Lin, D. G. Wu et al., “Hsa_circ_0006948 enhances cancer progression and epithelial-mesenchymal transition through the miR-490-3p/HMGA2 axis in esophageal squamous cell carcinoma,” Aging-Us, vol. 11, no. 24, pp. 11937–11954, 2019.
View at: Publisher Site | Google Scholar
Y. Shi, Z. Guo, N. Fang et al., “hsa_circ_0006168 sponges miR-100 and regulates mTOR to promote the proliferation, migration and invasion of esophageal squamous cell carcinoma,” Biomedicine & Pharmacotherapy, vol. 117, article 109151, 2019.
View at: Publisher Site | Google Scholar
Y. Xing, W. J. Zha, X. M. Li et al., “Circular RNA circ-Foxo3 inhibits esophageal squamous cell cancer progression via the miR-23a/PTEN axis,” Journal of Cellular Biochemistry, vol. 121, pp. 2595–2605, 2019.
View at: Google Scholar
Z. Q. Xu, X. J. Tie, N. Li, Z. Y. Yi, F. Q. Shen, and Y. Zhang, “Circular RNA hsa_circ_0000654 promotes esophageal squamous cell carcinoma progression by regulating the miR-149-5p/IL-6/STAT3 pathway,” IUBMB Life, vol. 72, no. 3, pp. 426–439, 2020.
View at: Publisher Site | Google Scholar
Z. Zhang, X. Li, F. Xiong, Z. Ren, and Y. Han, “Hsa_circ_0012563 promotes migration and invasion of esophageal squamous cell carcinoma by regulating XRCC1/EMT pathway,” Journal of Clinical Laboratory Analysis, vol. 34, no. 8, article e23308, 2020.
View at: Publisher Site | Google Scholar
Z. Zhang, W. Lin, L. Gao et al., “Hsa_circ_0004370 promotes esophageal cancer progression through miR-1294/LASP1 pathway,” Bioscience Reports, vol. 39, no. 5, 2019.
View at: Publisher Site | Google Scholar
G. Tian, G. Li, L. Guan, Z. Wang, and N. Li, “Prognostic value of circular RNA ciRS-7 in various cancers: a PRISMA-compliant meta-analysis,” BioMed Research International, vol. 2020, Article ID 1487609, 9 pages, 2020.
View at: Publisher Site | Google Scholar
X. Huang, W. Zhang, and Z. Shao, “Prognostic and diagnostic significance of circRNAs expression in lung cancer,” Journal of Cellular Physiology, vol. 234, no. 10, pp. 18459–18465, 2019.
View at: Publisher Site | Google Scholar
C. Lu, X. Shi, A. Y. Wang et al., “RNA-Seq profiling of circular RNAs in human laryngeal squamous cell carcinomas,” Molecular Cancer, vol. 17, no. 1, p. 86, 2018.
View at: Publisher Site | Google Scholar
J. Yuan, D. Guo, X. Li, and J. Chen, “Prognostic and diagnostic value of circRNA expression in colorectal carcinoma: a meta-analysis,” BMC Cancer, vol. 20, no. 1, p. 448, 2020.
View at: Publisher Site | Google Scholar
C. Niu, L. Zhao, X. Guo, Y. Shen, Y. Shao, and F. Liu, “Diagnostic accuracy of circRNAs in esophageal cancer: a meta-analysis,” Disease Markers, vol. 2019, Article ID 9673129, 7 pages, 2019.
View at: Publisher Site | Google Scholar
K. Danza, N. Silvestris, G. Simone et al., “Role of miR-27a, miR-181a and miR-20b in gastric cancer hypoxia-induced chemoresistance,” Cancer Biology & Therapy, vol. 17, no. 4, pp. 400–406, 2016.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2020 Hong Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

264

Downloads

978

Citations