<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">IJCM</journal-id><journal-title-group><journal-title>International Journal of Clinical Medicine</journal-title></journal-title-group><issn pub-type="epub">2158-284X</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ijcm.2024.153009</article-id><article-id pub-id-type="publisher-id">IJCM-132105</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  A Meta-Analysis of the Prognostic and Clinicopathological Significance of circZFR in Human Gastrointestinal Cancers
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Christian</surname><given-names>Cedric Bongolo</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Erick</surname><given-names>Thokerunga</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yu</surname><given-names>Zhang</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jian-Cheng</surname><given-names>Tu</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Wuhan Life Origin Biotech Joint Stock Co, Ltd., Wuhan, China</addr-line></aff><aff id="aff1"><addr-line>College of Life Sciences and Technology, Huazhong Agricultural University, Wuhan, China</addr-line></aff><pub-date pub-type="epub"><day>21</day><month>03</month><year>2024</year></pub-date><volume>15</volume><issue>03</issue><fpage>134</fpage><lpage>144</lpage><history><date date-type="received"><day>20,</day>	<month>February</month>	<year>2024</year></date><date date-type="rev-recd"><day>25,</day>	<month>March</month>	<year>2024</year>	</date><date date-type="accepted"><day>28,</day>	<month>March</month>	<year>2024</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Background: Studies of gastrointestinal (GIT) cancers have shown that circZFR could be involved in the development and progression of various GIT cancers. However, small sample sizes limit the clinical significance of these studies. Here, a meta-analysis was conducted to ascertain the actual involvement of circZFR in the development and prognosis of GIT cancers. 
  Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched up to December 31, 2023. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were pooled to evaluate the association between circZFR expression and overall survival (OS). Publication bias was measured using the funnel plot and Egger’s test. 
  Results: 10 studies having 659 participants were enrolled for meta-analysis. High circZFR expression was associated with poor OS (HR = 1.4, 95% CI: 1.20, 1.70). High circZFR expression also predicted larger tumor size (OR = 4.38, 95% CI 2.65, 7.25), advanced clinical stage (OR = 5.33, 95% CI 3.10, 9.16), and tendency for distant metastasis (OR = 2.89, 95% CI: 1.62, 5.11), but was not related to age, gender, and histological grade. 
  Conclusions: In summary, high circZFR expression was associated with poor OS, larger tumor size, advanced stage cancer and tendency for distant metastasis. These findings suggested that circZFR could be a prognostic marker for GIT cancers.
 
</p></abstract><kwd-group><kwd>CircZFR</kwd><kwd> Gastrointestinal</kwd><kwd> Prognostic</kwd><kwd> Significance</kwd><kwd> Meta-Analysis</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Background</title><p>In humans, approximately 93% of the genome can be transcribed into RNA yet less than 2% are capable of being translated into proteins. The rest are termed non-coding RNAs [<xref ref-type="bibr" rid="scirp.132105-ref1">1</xref>] . Among these are circular RNAs (circRNAs) [<xref ref-type="bibr" rid="scirp.132105-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref3">3</xref>] characterized by highly conserved closed loop structures that lack a free 5 cap and 3' tail, making them resistant to degradation by exonucleases. While most circRNAs are derived from exons and found in the cell cytoplasm, their mechanism of formation remains largely unknown [<xref ref-type="bibr" rid="scirp.132105-ref4">4</xref>] .</p><p>CircRNAs primarily carry out their biological activities by acting as competing endogenous RNAs (ceRNAs), helping to sponge miRNAs, control transcription, and translation and carry out other epigenetic tasks. For instance, upregulation of circCDR1as in gastric cancer suppresses miR-7 activity which leads to more aggressive oncogenic phenotype mediated by PTEN/PI3K/AKT pathway [<xref ref-type="bibr" rid="scirp.132105-ref5">5</xref>] . Various studies have demonstrated their ability to regulate aging [<xref ref-type="bibr" rid="scirp.132105-ref6">6</xref>] , diabetes [<xref ref-type="bibr" rid="scirp.132105-ref7">7</xref>] , and various tumors [<xref ref-type="bibr" rid="scirp.132105-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref10">10</xref>] . In tumors, the involvement of circRNAs has been demonstrated in tumor development, proliferation, and metastasis [<xref ref-type="bibr" rid="scirp.132105-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref11">11</xref>] . Recent studies have also demonstrated their involvement in tumor resistance to chemotherapy [<xref ref-type="bibr" rid="scirp.132105-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref13">13</xref>] .</p><p>Circular RNA zinc finger RNA-binding protein (Circ-ZFR) is a transcription product of zinc finger RNA-binding protein (ZFR) gene mapped to chromosome 5p13.3. Studies of gastrointestinal (GIT) cancers have shown that it could be involved in the development and progression of various GIT cancers such as hepatocellular carcinoma (HCC) [<xref ref-type="bibr" rid="scirp.132105-ref14">14</xref>] , gastric cancer (GC) [<xref ref-type="bibr" rid="scirp.132105-ref15">15</xref>] , and colorectal cancer (CRC) [<xref ref-type="bibr" rid="scirp.132105-ref16">16</xref>] among others. While the majority of these studies have demonstrated its oncogenic property, their small sample sizes limit their clinical significance. In this study, we sought to conduct a meta-analysis of all these studies to ascertain the actual involvement of circZFR in the development and prognosis of GIT cancers.</p></sec><sec id="s2"><title>2. Methods</title><p>Records search strategy</p><p>This meta-analysis was conducted according to the 2020 updated Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) [<xref ref-type="bibr" rid="scirp.132105-ref17">17</xref>] . A comprehensive database search was conducted by two independent reviewers (CCB and ET) in PubMed, Embase, Web of Science, and the Cochrane Library up to December 31, 2023. The key items in the search strategy were: “circZFR” OR “circ_ZFR” OR “circ-ZFR” OR “circRNA ZFR” OR “circular RNA ZFR” OR “circ_0072088” OR “circ_0072083” OR “Circ_103809” OR “circRNA_103809” OR “Hsa_circRNA_103809” OR “Circular RNA hsa_circRNA_103809”. Additionally, references of included articles were manually searched for relevant articles, and a general search on google and google scholar were conducted for articles missed in the database search.</p><p>Inclusion and exclusion criteria</p><p>The inclusion and exclusion criteria were as follows: Inclusion criteria: 1) Patients definitely diagnosed with HCC by histopathology; 2) studies that focused on clinical diagnostic or prognostic value of circZFR in HCC; 3) studies where circZFR was assigned to high expression group (high) or low expression group (low) based on its relative expression level; 4) studies that provided enough information on the correlation between circZFR expression level and overall survival (HRs with 95% CIs) or clinical characteristics (age, gender, stage, grade, and so on). Studies were excluded if: 1) they were duplicate publications; 2) focused on the structures or functions of circZFR, without any clinical diagnostic or prognostic information; 3) had non-extractable data; 4) and had no original data e.g. reviews and meta-analysis.</p><p>Data extraction and study quality assessment</p><p>Included studies were independently assessed in detail by two investigators (CCB and ET) for data extraction. Each investigator extracted data independently and any discrepancies were settled by consensus. None of the studies was an RCT. The baseline data extracted from each study were: 1) first author name and year of study, country, cancer type, clinical stage, tumor size, cut-off value, follow-up time, detection method, adjuvant therapy before surgery, survival analysis method, and outcome measure method; 2) hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) of circZFR for OS or clinicopathologic parameters. For studies that did not directly present HRs, the software Engauge Digitizer (version 4.1) was used to calculate it from the Kaplan-Meier curve. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) [<xref ref-type="bibr" rid="scirp.132105-ref18">18</xref>] .</p><p>Data synthesis and statistical analysis</p><p>The statistical analyses were conducted in Review Manager (RevMan 5.4). HRs or ORs with corresponding 95% CIs were used to describe the relationship between circZFR expression and the prognosis or clinical characteristics. The chi-squared test and I<sup>2</sup> statistics was used to assess the heterogeneity among studies. A value of p &lt; 0.05, I<sup>2</sup> &gt; 50% was considered to be study heterogeneity. Random effect model was used since the studies had varying methodologies. The funnel plot and Egger’s test was used to estimate the potential publication bias. A P value of p &lt; 0.05 was considered statistically significant.</p></sec><sec id="s3"><title>3. Results</title><p>Study selection criteria</p><p>Thorough database search yielded 89 studies in total, with 49 duplicates that were promptly excluded. 3 studies were reviews and so excluded as well. The remaining 37 studies had their full-text articles extracted and thoroughly assessed. 24 of them did not have clinical analyses while 3 had unextractable data. These were all excluded leaving 10 studies [<xref ref-type="bibr" rid="scirp.132105-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref19">19</xref>] - [<xref ref-type="bibr" rid="scirp.132105-ref26">26</xref>] all from China for final inclusion in the meta-analysis. All the studies combined had a total of 659 participants. The selection flow chart is presented in <xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref>.</p><p>Description of included studies</p><p>Detailed information on the enrolled studies is presented in <xref ref-type="table" rid="table1">Table 1</xref>. Studies</p><p>were published between 2017 to 2021, and all were conducted in China. CircZFR expression level was detected by quantitative real-time polymerase chain reaction (qRT-PCR) in all studies with the sample size ranging from 30 to 170. Analyses were both univariate and multivariate. Outcome measures were clinicopathological parameters (CP) and overall survival (OS). Only 4 studies mentioned the overall follow up time of the patients, all 60 months and more. Mean and median expression of circZFR were used as cut-off values. NOS score in all the studies was ≥ 7, indicating high overall quality of the studies.</p><p>Association between circZFR expression and OS</p><p>Four studies [<xref ref-type="bibr" rid="scirp.132105-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref21">21</xref>] comprising 360 participants qualified for pooled OS analysis. The studies were generally homogeneous (I<sup>2</sup> = 0%, p = 0.94). The OS results indicated that high expression of circZFR was associated with relatively poor OS (HR = 1.4, 95% CI: 1.20, 1.70) (<xref ref-type="fig" rid="fig2"><xref ref-type="fig" rid="fig">Figure </xref>2</xref>).</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Summary of the main characteristics of included studies</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Author</th><th align="center" valign="middle" >Country</th><th align="center" valign="middle" >Cancer type</th><th align="center" valign="middle" >Clinical stage</th><th align="center" valign="middle" >Sample size</th><th align="center" valign="middle" >Cut off value</th><th align="center" valign="middle" >Follow up (months)</th><th align="center" valign="middle" >Detection method</th><th align="center" valign="middle" >Adjuvant therapy</th><th align="center" valign="middle" >Survival analysis</th><th align="center" valign="middle" >Outcome measure</th><th align="center" valign="middle" >NOS</th></tr></thead><tr><td align="center" valign="middle" >Cedric, 2020</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >T1 - T4</td><td align="center" valign="middle" >62</td><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr><tr><td align="center" valign="middle" >Li, 2021</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >I-III</td><td align="center" valign="middle" >49</td><td align="center" valign="middle" >NA</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr><tr><td align="center" valign="middle" >Lin, 2021</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >Median</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Multivariate</td><td align="center" valign="middle" >OS, CP</td><td align="center" valign="middle" >9</td></tr><tr><td align="center" valign="middle" >Tan, 2019</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >OS</td><td align="center" valign="middle" >8</td></tr><tr><td align="center" valign="middle" >Xu, 2021</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >NA</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr><tr><td align="center" valign="middle" >Yang, 2019</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >Median</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr><tr><td align="center" valign="middle" >Zhan, 2020</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >HCC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >NA</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >OS, CP</td><td align="center" valign="middle" >9</td></tr><tr><td align="center" valign="middle" >Fang, 2020</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >ESCC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >58</td><td align="center" valign="middle" >Median</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr><tr><td align="center" valign="middle" >Huang, 2020</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >GC</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >NA</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >OS</td><td align="center" valign="middle" >8</td></tr><tr><td align="center" valign="middle" >Zhang, 2017</td><td align="center" valign="middle" >China</td><td align="center" valign="middle" >CRC</td><td align="center" valign="middle" >I-IV</td><td align="center" valign="middle" >170</td><td align="center" valign="middle" >NA</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >qRT-PCR</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Univariate</td><td align="center" valign="middle" >CP</td><td align="center" valign="middle" >7</td></tr></tbody></table></table-wrap><p>Abbreviations: CRC: colorectal cancer; CP: clinicopathological parameters; ESCC: esophageal squamous; GC: gastric cancer; HCC: hepatocellular carcinoma; N/A: not available; NOS: Newcastle-Ottawa Scale; OS: overall survival; qRT-PCR: quantitative real-time polymerase chain reaction.</p><p>Association between circZFR expression and clinicopathological parameters</p><p>Age, gender, tumor size, clinical stage, distant metastasis (DM), lymph node metastasis (LNM), and histology grade were the clinicopathological parameters analyzed to evaluate their correlation with circZFR expression (<xref ref-type="table" rid="table2">Table 2</xref>). Notably, six studies enrolled to explore the correlation between circZFR expression and tumor size, demonstrating that higher circZFR expression predicted larger tumor size (OR = 4.38, 95% CI 2.65, 7.25). Similarly, the upregulation of circZFR expression indicated advanced clinical stage (OR = 5.33, 95% CI 3.10, 9.16), and distant metastasis DM (OR = 2.89, 95% 1.62, 5.11) (<xref ref-type="fig" rid="fig3"><xref ref-type="fig" rid="fig">Figure </xref>3</xref>). Statistically insignificant association were found between circZFR expression and age (OR = 1.44, 95% CI 0.94, 2.22), gender (OR = 1.06, 95% CI 0.72, 1.57), and histological grade (OR = 1.75, 95% CI 0.52, 5.93) (<xref ref-type="fig" rid="fig">Figure </xref>S1).</p><p>Publication bias analysis</p><p>The potential for publication bias was estimated using the funnel plot method and Egger’s test. The results showed no significant publication bias as indicated</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Association between circZFR and other clinicopathological parameters</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Subgroup</th><th align="center" valign="middle" >Studies</th><th align="center" valign="middle" >Total participants</th><th align="center" valign="middle" >Odds ratio (95% CI)</th><th align="center" valign="middle" >P value</th><th align="center" valign="middle" >Model</th><th align="center" valign="middle" >Heterogeneity (I<sup>2</sup>)</th></tr></thead><tr><td align="center" valign="middle" >Age</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >479</td><td align="center" valign="middle" >1.44 (0.94 - 2.22)</td><td align="center" valign="middle" >0.09</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >6%</td></tr><tr><td align="center" valign="middle" >Sex</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >519</td><td align="center" valign="middle" >1.06 (0.72 - 1.57)</td><td align="center" valign="middle" >0.77</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >0%</td></tr><tr><td align="center" valign="middle" >Tumor size</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >397</td><td align="center" valign="middle" >4.38 (2.65 - 7.25)</td><td align="center" valign="middle" >0.0001</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >0%</td></tr><tr><td align="center" valign="middle" >Clinical stage</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >397</td><td align="center" valign="middle" >5.33 (3.10 - 9.16)</td><td align="center" valign="middle" >0.00001</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >0%</td></tr><tr><td align="center" valign="middle" >LNM stage</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >290</td><td align="center" valign="middle" >2.89 (1.62 - 5.11)</td><td align="center" valign="middle" >0.003</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >0%</td></tr><tr><td align="center" valign="middle" >DM</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >232</td><td align="center" valign="middle" >2.09 (1.01 - 4.32)</td><td align="center" valign="middle" >0.05</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >0%</td></tr><tr><td align="center" valign="middle" >Histology Grade</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >258</td><td align="center" valign="middle" >1.75 (0.52 - 5.93)</td><td align="center" valign="middle" >0.37</td><td align="center" valign="middle" >Random</td><td align="center" valign="middle" >73%</td></tr></tbody></table></table-wrap><p>Abbreviations: CI: confidence interval; DM: distant metastasis; LNM: lymph node metastasis; OR: odds ratio.</p><p>by the symmetrical distribution of study points in the funnel plot (<xref ref-type="fig" rid="fig">Figure </xref>S2). Furthermore, Egger’s test (p = 0.172) indicted no publication bias.</p></sec><sec id="s4"><title>4. Discussion</title><p>Recent studies indicate that circRNAs possess potentials for cancer prognostic and treatment applications given their stability in body fluids such as plasma and serum, and specificity in certain cancers [<xref ref-type="bibr" rid="scirp.132105-ref27">27</xref>] . Circ ZFR is one of such circRNAs whose potential as a cancer driver gene has been verified in different studies. It is overexpressed in some GIT cancers [<xref ref-type="bibr" rid="scirp.132105-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.132105-ref20">20</xref>] , while under expressed in others [<xref ref-type="bibr" rid="scirp.132105-ref26">26</xref>] . Analysis of its expression indicates strong association with certain clinicopathological characteristics in GIT cancers, making it a potential biomarker for prognostic prediction of these cancers.</p><p>In this meta-analysis, we assessed the association between CircZFR and GIT cancers. In the first step, we determined the correlation between circZFR expression and the overall survival (OS) of patients with GIT cancers. The pooled HR revealed that high circZFR expression was associated with poor OS. This was true whether the cut-off values of CircZFR expression were captured in mean or median in the original studies. Indeed, circZFR overexpression has been shown to promote cell proliferation, migration and invasion in GIT cancers such as esophageal squamous cell carcinoma [<xref ref-type="bibr" rid="scirp.132105-ref22">22</xref>] , hepatocellular carcinoma [<xref ref-type="bibr" rid="scirp.132105-ref24">24</xref>] and gastric cancer [<xref ref-type="bibr" rid="scirp.132105-ref15">15</xref>] among others.</p><p>In relation to other major patient characteristics, we evaluated the association between circZFR expression and the patients’ age, gender, tumor size, clinical stage, distant metastasis and histology grade. Our findings showed that higher circZFR expression was correlated with larger tumor size, advanced clinical stage, and distant metastasis. Statistically insignificant associations were noted in age, gender and histological grades. While circRNAs effect their biological functions by acting as miRNA molecular sponge, or regulating transcription of genes, and sometimes translation into proteins or small peptides, the function and mechanism of action of circZFR in promoting GIT cancers is still largely unclear and needs further research to unravel.</p><p>In terms of heterogeneity, the studies were largely homogenous as demonstrated by the I<sup>2</sup> values in the various forest plots. This is likely because all the studies were conducted in China and most had similar designs. Similarly, there was no publication bias as indicated by the symmetrical shape of the funnel plot and the result of the Egger’s test. These findings improve the reliability of the meta-analysis.</p><p>This study had the following limitations that may affect interpretation. Firstly, all the included participants were from China, making generalization of results across different regions of the world difficult. Secondly, only four studies qualified for the prognosis meta-analysis, which greatly limited the wide application of the meta-analysis results. Finally, since many studies never reported HRs with their 95% CIs in the main articles, we extracted these values from the Kaplan-Meier curves. This could have an effect on their accuracy.</p></sec><sec id="s5"><title>5. Conclusion</title><p>In summary, this meta-analysis demonstrated that upregulation of circ-ZFR expression is highly correlated with poor prognosis of GIT cancers. It is also correlated with certain clinicopathological parameters such as larger tumor size, advanced clinical stage, and distant metastasis among patients of Chinese origin. This demonstrates that circZFR could be a prognostic biomarker for GIT cancers. However, large-scale studies from different regions of the world will be required to verify these results.</p></sec><sec id="s6"><title>Authors’ Contributions</title><p>CCB designed the study, performed the literature retrieval, data analysis, interpretation and drafted the manuscript. ET contributed to the study methodology, performed literature retrieval and data analysis and reviewed the manuscript. ZY participated in the data analysis and assisted in creating the figures and reviewed the manuscript. JCT supervised the study. All authors read and approved the final manuscript.</p></sec><sec id="s7"><title>Funding</title><p>This study was supported by Hubei Provincial Science and Technology (Project 2022BAD098) and Postdoctoral Programme of Wuhan Life Origin Biotech Joint stock fund.</p></sec><sec id="s8"><title>Availability of Data and Materials</title><p>The dataset used and analyzed during the current study are available from the corresponding author on reasonable request.</p></sec><sec id="s9"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s10"><title>Cite this paper</title><p>Bongolo, C.C., Thokerunga, E., Zhang, Y. and Tu, J.-C. (2024) A Meta-Analysis of the Prognostic and Clinicopathological Significance of circZFR in Human Gastrointestinal Cancers. International Journal of Clinical Medicine, 15, 134-144. https://doi.org/10.4236/ijcm.2024.153009</p></sec><sec id="s11"><title>Supplementary</title></sec></body><back><ref-list><title>References</title><ref id="scirp.132105-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Dunham, I., et al. (2012) An Integrated Encyclopedia of DNA Elements in the Human Genome. Nature, 489, 57-74. https://doi.org/10.1038/nature11247</mixed-citation></ref><ref id="scirp.132105-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Capel, B., et al. (1993) Circular Transcripts of the Testis-Determining Gene Sry in Adult Mouse Testis. Cell, 73, 1019-1030.https://doi.org/10.1016/0092-8674(93)90279-Y</mixed-citation></ref><ref id="scirp.132105-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Cocquerelle, C., Mascrez, B., Hétuin, D. and Bailleul, B. (1993) Mis-Splicing Yields Circular RNA Molecules. The FASEB Journal, 7, 155-160.https://doi.org/10.1096/fasebj.7.1.7678559</mixed-citation></ref><ref id="scirp.132105-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Chen L.-L. and Yang, L. (2015) Regulation of circRNA Biogenesis. RNA Biology, 12, 381-388. https://doi.org/10.1080/15476286.2015.1020271</mixed-citation></ref><ref id="scirp.132105-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Pan, H., et al. (2018) Overexpression of Circular RNA ciRS-7 Abrogates the Tumor Suppressive Effect of miR-7 on Gastric Cancer via PTEN/PI3K/AKT Signaling Pathway. Journal of Cellular Biochemistry, 119, 440-446.https://doi.org/10.1002/jcb.26201</mixed-citation></ref><ref id="scirp.132105-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Knupp, D. and Miura, P. (2018) CircRNA Accumulation: A New Hallmark of Aging? Mechanisms of Ageing and Development, 173, 71-79.https://doi.org/10.1016/j.mad.2018.05.001</mixed-citation></ref><ref id="scirp.132105-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Yang, F., et al. (2020) High-Throughput Sequencing and Exploration of the lncRNA-circRNA-miRNA-mRNA Network in Type 2 Diabetes Mellitus. BioMed Research International, 2020, Article ID: 8162524. https://doi.org/10.1155/2020/8162524</mixed-citation></ref><ref id="scirp.132105-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Fu, L., Jiang, Z., Li, T., Hu, Y. and Guo, J. (2018) Circular RNAs in Hepatocellular Carcinoma: Functions and Implications. Cancer Medicine, 7, 3101-3109.https://doi.org/10.1002/cam4.1574</mixed-citation></ref><ref id="scirp.132105-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Huang, W., et al. (2020) Circular RNA cESRP1 Sensitises Small Cell Lung Cancer Cells to Chemotherapy by Sponging miR-93-5p to Inhibit TGF-β Signaling. Cell Death &amp; Differentiation, 27, 1709-1727. https://doi.org/10.1038/s41418-019-0455-x</mixed-citation></ref><ref id="scirp.132105-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Shi, X., Wang, B., Feng, X., Xu, Y., Lu, K. and Sun, M. (2019) CircRNAs and Exosomes: A Mysterious Frontier for Human Cancer. Molecular Therapy: Nucleic Acids, 19, 384-392. https://doi.org/10.1016/j.omtn.2019.11.023</mixed-citation></ref><ref id="scirp.132105-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Meng, S., et al. (2017) CircRNA: Functions and Properties of a Novel Potential Biomarker for Cancer. Molecular Cancer, 16, Article No. 94.https://doi.org/10.1186/s12943-017-0663-2</mixed-citation></ref><ref id="scirp.132105-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Zhao, Z., Ji, M., Wang, Q., He, N. and Li, Y. (2019) Circular RNA Cdr1as Upregulates SCAI to Suppress Cisplatin Resistance in Ovarian Cancer via miR-1270 Suppression. Molecular Therapy: Nucleic Acids, 18, 24-33.https://doi.org/10.1016/j.omtn.2019.07.012</mixed-citation></ref><ref id="scirp.132105-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Kun-Peng, Z., Xiao-Long, M., Lei, Z., Chun-Lin, Z., Jian-Ping, H. and Tai-Cheng, Z. (2018) Screening Circular RNA Related to Chemotherapeutic Resistance in Osteosarcoma by RNA Sequencing. Epigenomics, 10, 1327-1346.https://doi.org/10.2217/epi-2018-0023</mixed-citation></ref><ref id="scirp.132105-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Cedric, B.C., Souraka, T.D.M., Feng, Y.-L., Kisembo, P. and Tu, J.-C. (2020) CircRNA ZFR Stimulates the Proliferation of Hepatocellular Carcinoma through Upregulating MAP2K1. European Review for Medical and Pharmacological Sciences, 24, 9924-9931.</mixed-citation></ref><ref id="scirp.132105-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Huang, S.-S., Guo, W.-X. and Ren, M.-S. (2020) Circular RNA hsa_circ_103809 Promotes Cell Migration and Invasion of Gastric Cancer Cells by Binding to microRNA-101-3p. European Review for Medical and Pharmacological Sciences, 24, 6064-6071.</mixed-citation></ref><ref id="scirp.132105-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Tan, Y., Wang, K. and Kong, Y. (2022) Circular RNA ZFR Promotes Cell Cycle Arrest and Apoptosis of Colorectal Cancer Cells via the miR-147a/CACUL1 Axis. Journal of Gastrointestinal Oncology, 13, 1793-1804.https://doi.org/10.21037/jgo-22-672</mixed-citation></ref><ref id="scirp.132105-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Page, M.J., et al. (2021) The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ, 372, Article n71.https://doi.org/10.1136/bmj.n71</mixed-citation></ref><ref id="scirp.132105-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Lo, C.K.-L., Mertz, D. and Loeb, M. (2014) Newcastle-Ottawa Scale: Comparing Reviewers’ to Authors’ Assessments. BMC Medical Research Methodology, 14, Article No. 45. https://doi.org/10.1186/1471-2288-14-45</mixed-citation></ref><ref id="scirp.132105-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Lin, Y., Zheng, Z.-H., Wang, J.-X., Zhao, Z. and Peng, T.-Y. (2021) Tumor Cell-Derived Exosomal Circ-0072088 Suppresses Migration and Invasion of Hepatic Carcinoma Cells Through Regulating MMP-16. Frontiers in Cell and Developmental Biology, 9, Article 726323. https://doi.org/10.3389/fcell.2021.726323</mixed-citation></ref><ref id="scirp.132105-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Tan, A., Li, Q. and Chen, L. (2019) CircZFR Promotes Hepatocellular Carcinoma Progression through Regulating miR-3619-5p/CTNNB1 Axis and Activating Wnt/β-Catenin Pathway. Archives of Biochemistry and Biophysics, 661, 196-202.https://doi.org/10.1016/j.abb.2018.11.020</mixed-citation></ref><ref id="scirp.132105-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Zhan, W., et al. (2020) Circular RNA hsa_circRNA_103809 Promoted Hepatocellular Carcinoma Development by Regulating miR-377-3p/FGFR1/ERK Axis. Journal of Cellular Physiology, 235, 1733-1745. https://doi.org/10.1002/jcp.29092</mixed-citation></ref><ref id="scirp.132105-ref22"><label>22</label><mixed-citation publication-type="other" xlink:type="simple">Fang, N., Shi, Y., Fan, Y., Long, T., Shu, Y. and Zhou, J. (2020) Circ_0072088 Promotes Proliferation, Migration, and Invasion of Esophageal Squamous Cell Cancer by Absorbing miR-377. Journal of Oncology, 2020, Article ID: 8967126.https://doi.org/10.1155/2020/8967126</mixed-citation></ref><ref id="scirp.132105-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Li, L., Xiao, C., He, K. and Xiang, G. (2021) Circ_0072088 Promotes Progression of Hepatocellular Carcinoma by Activating JAK2/STAT3 Signaling Pathway via miR-375. IUBMB Life, 73, 1153-1165. https://doi.org/10.1002/iub.2520</mixed-citation></ref><ref id="scirp.132105-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">Xu, R., Yin, S., Zheng, M., Pei, X. and Ji, X. (2021) Circular RNA circZFR Promotes Hepatocellular Carcinoma Progression by Regulating miR-375/HMGA2 Axis. Digestive Diseases and Sciences, 66, 4361-4373.https://doi.org/10.1007/s10620-020-06805-2</mixed-citation></ref><ref id="scirp.132105-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">Yang, X., Liu, L., Zou, H., Zheng, Y.-W. and Wang, K.-P. (2019) CircZFR Promotes Cell Proliferation and Migration by Regulating miR-511/AKT1 Axis in Hepatocellular Carcinoma. Digestive and Liver Disease, 51, 1446-1455.https://doi.org/10.1016/j.dld.2019.04.012</mixed-citation></ref><ref id="scirp.132105-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">Zhang, P., et al. (2017) Identification of Differentially Expressed Circular RNAS in Human Colorectal Cancer. Tumor Biology, 39, 1-10.https://doi.org/10.1177/1010428317694546</mixed-citation></ref><ref id="scirp.132105-ref27"><label>27</label><mixed-citation publication-type="other" xlink:type="simple">Verduci, L., Strano, S., Yarden, Y. and Blandino, G. (2019) The circRNA-microRNA code: Emerging Implications for Cancer Diagnosis and Treatment. Molecular Oncology, 13, 669-680. https://doi.org/10.1002/1878-0261.12468</mixed-citation></ref></ref-list></back></article>