The association between HIC1 methylation and ovarian cancer: a meta-analysis

Objective : HIC1 is a tumor suppressor gene (TSG) located in the 17p13.3 region that encodes a transcriptional repressor. Research published over the past few years indicates that HIC1 methylation is a critical factor in the oncogenesis of ovarian cancer (OC). However, previous studies had only small sample sizes and thus were unable to reach firm conclusions. Data Sources : Therefore, we performed a meta-analysis to further investigate the association between HIC1 methylation and OC. Studies related to HIC1 methylation and OC were identified from searches of PubMed, EMBASE, Medline and CNKI. Methods of Study Selection : Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between the two factors. Subgroup analysis and Begg’s test were used to evaluate heterogeneity and publication bias. From 591 studies, 7 were selected for meta-analysis and these comprised 455 cases and 278 controls. Tabulation, Integration and Results : A significant association between HIC1 methylation and OC was found under the fixed-effects model (OR = 4.306, 95% CI = 2.846 to 6.515). Subgroup analysis of the control type yielded a less tight association (OR = 4.143, p = 0.147, I 2 = 41.1%). Finally, we conducted analysis of the Cancer Genome Atlas (TCGA) data and found higher HIC1 methylation levels in OC compared to adjacent non-tumor tissue. Conclusion : In conclusion, this meta-analysis found that HIC1 methylation was strongly associated with OC.


Introduction
Ovarian cancer (OC) is a lethal gynecologic malignancy comprised of epithelial cancer in 90% of cases [1,2]. OC is the 5th leading cause of cancer death in women, with 21,990 new cases and 15,460 deaths annually in the US [3]. There are no efficient screening programs for OC and in the early stages these patients are asymptomatic. Hence, cases are generally diagnosed with late stage disease where the cancer has disseminated within the peritoneal cavity and making it is impossible to achieve complete surgical removal [4]. So far, only a small number of risk factors have been identified and these include age and a family history of ovarian and/or breast cancer. Parity and the use of oral contraceptives are likely protective factors [5]. Recently, it was reported that methylation of some tumor suppressor genes may play a significant role in OC, including BRCA1 [6], HOXA9 [7], RASSF1A [8], SPARC [9] and HIC1 [10].
HIC1 is a tumor suppressor gene (TSG) that encodes a transcriptional repressor widely expressed in normal tissues. It is located in 17p13.3, a region frequently hypermethylated or deleted in many human cancer types [11][12][13][14][15][16]. HIC1 is methylated in about one third of OC, suggesting it may have a TSG role in this tumor type [10]. Other studies have also shown strong links between HIC1 promoter methylation and the development of OC. Reversal of HIC1 promoter methylation in OC may thus provide a rational basis for the clinical treatment of OC.
Various case-control and cohort studies have demonstrated a role for HIC1 genetic variants in OC. In the present study, we conducted a meta-analysis of all relevant studies using an updated and powerful statistical method in order to study the association between HIC1 methylation and OC.

Search strategy
Four reviewers divided into two groups and then searched four databases independently for articles related to OC and HIC1 methylation. The two groups combined their results after assessment and discussion. Original articles published up to 2020 were identified by the use of search terms including 'ovarian' AND 'cancer OR tumor' AND 'HIC1' AND 'methylation'. The search process was performed without restrictions on the publication year or language.

Inclusion and exclusion criteria
The title, abstract and keywords from 591 studies originally identified by the search (130 from PubMed, 188 from EMBASE, 63 from Medline and 210 from CNKI) were further scanned to identify studies on OC and HIC1 methylation and to exclude irrelevant studies and reviews. To prevent inclusion bias, studies from the primary screen were downloaded for full-text review. Eligible studies were required to meet the following inclusion criteria: (A) OC pa-tients were diagnosed by pathology; (B) studies evaluated the association between OC and HIC1 methylation; (C) the number of OC cases in the study was >20. Studies were eliminated if they met one or more of the following exclusion criteria: (A) reviews; (B) cases only included cell lines and animals; (C) cases without controls. After the removal of duplicates from the databases, the remaining studies were selected for data extraction and quality assessment.

Data extraction and quality assessment
Information extracted from the eligible studies was as follows: first author, year of publication, country and region of study, study population, sample size, frequency of HIC1 methylation in case and control groups, cancer stage, methylation detection method, and the tissue type used for controls. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of eligible studies. A study that met one of the 9 items listed above scored one point, with the highest possible score being 9. If a study did not include one of the 9 items, that point was considered to be lost. Only studies that reached a score of 5 points or more were included in the meta-analysis.

Statistical analyses
Statistical variables were calculated using STATA (Version.12.0, StataCorp LLC, TX, USA). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association between HIC1 methylation and OC. Methylation profiles (Illumina Human Methylation 27) and the corresponding clinical data set for 11 OC cases and 11 controls were downloaded from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/). Heterogeneity was evaluated with Chi-square test tests and the I 2 value. I 2 = 0-50% indicates no or moderate heterogeneity, while I 2 >50% indicates significant heterogeneity. The fixed-effect model was used if there was no significant heterogeneity, otherwise the random effects model model was used. Subgroup analysis was performed to evaluate the source of heterogeneity. Begg's test and Egger's test were performed to assess the possibility of publication bias. Asymmetry of Begg's funnel plot and a p-value in Begg's test of <0.05 were considered to indicate the existence of publication bias.

Study selection
Following the search strategy described above, 591 studies were initially identified from the databases. Two separate review groups independently identified the studies for exclusion and then combined their results. A total of 174 studies were excluded due to being duplicates. After scanning the title and abstract of the remaining 417 studies, 398 were deemed not applicable to this research (237 irrelevant articles, 154 reviews, 4 meta-analyses and 3 others). Next, the full text for the 19 potentially relevant articles was scrutinized. Of these, 6 articles contained no data on HIC1, 3 were not focused on HIC1 methylation, one was not a full text article, one was not written in English and another did not include controls. Following exclusion of these 12 papers, 7 papers were deemed eligible for final quantitative assessment (Fig. 1).

Description of studies
Relevant information for the 7 studies is presented in Table 1 (Ref. [9,11,[16][17][18][19][20]). All were published between 2001 and 2013 and included a total of 733 samples (455 cases and 278 controls). The sample size in each study ranged from 46 to 207 and the majority of patients were aged between 30 and 60 years. Two studies did not record patient age and one study [16] did not report the cancer stage. In the 6 studies that reported cancer stage, there were more early stage patients than advanced stage patients. Cases were either fresh cancer tissues obtained surgically from cancer patients, or archival cancer specimens. All studies used methylation-specific polymerase chain reaction (MSP) for the detection of HIC1 methylation. The control group was comprised of adjacent tissues (AT) from OC  patients, ovarian tissues from benign OC patients (BT), borderline tissues from OC patients (BLT), normal ovarian tissues (NT) and neoplasia of low malignant potential (LMP).

Meta-analysis
No significant heterogeneity was found using the Chisquared and I 2 tests (p = 0.456, I 2 <0.000). A fixed-effects model was used to analyze the association between HIC1 methylation and OC. The forest plot showed the frequency of HIC1 methylation was strongly associated with OC (OR = 4.306, 95% CI = 2.846 to 6.515) (Fig. 2).

Publication bias
Publication bias was assessed using Begg's test and Egger's test. As shown in Fig. 4, no significant publication bias was found, with the shape of the Begg's funnel plot being approximately symmetrical. The p-values from the Egger's test showed no publication bias in any comparison.

TCGA dataset analysis
To further explore the relationship between HIC1 methylation and OC, we evaluated publicly available methylation data for OC and adjacent tissues. As shown in Fig. 5, HIC1 methylation was more frequent in OC tissues than in normal controls (p < 0.01).

Discussion
OC is one of the leading causes of cancer-related deaths in women worldwide [21]. The identification of markers for early diagnosis and for prognosis is crucial in the clinical treatment of OC. DNA methylation is a common epigenetic alteration that occurs in the promoter region, 5 ′ and 3 ′ untranslated regions and exons of genes. Aberrant DNA methylation can inactivate tumor suppressor gene (TSG) function by silencing their expression in various human cancers, thereby promoting tumor development and progression [12,17,22]. Mounting evidence shows that abnormal DNA methylation of TSGs leads to downregulation of gene expression in OC [23,24]. Methylation of the HIC1 TSG disrupts its normal function and promotes the progression of various cancer types [13,14,[25][26][27].
Since the original report of HIC1 methylation in OC, discordant conclusions have been reached regarding its association with OC. Tam showed the frequency of HIC1 methylation in OC tissue was significantly higher than in non-malignant ovarian tissue [18]. Feng suggested that HIC1 methylation was more frequent in early stage OC compared to late stage OC [19]. However, a study by Ozdemir et al. [28] did not detect HIC1 methylation in any OC samples, in contrast to the above reports.
In the present work we evaluated 7 studies containing a total of 455 cases and 278 controls in order to investigate the relationship between HIC1 methylation and OC. In this meta-analysis, HIC1 methylation was strongly associated with OC (OR = 4.306, 95% CI = 2.846 to 6.515). Together with the results from subgroup analyses, we showed the HIC1 methylation level in OC cases was significantly higher than in controls. These results did not appear to be affected by publication bias. Moreover, results from the TCGA database also showed the HIC1 methylation level in OC tissue was significantly higher than in adjacent, nontumor tissues. The present work indicates that HIC1 methylation is strongly linked with OC, and is consistent with the results of previous studies [18][19][20].
Although we have identified an association between HIC1 methylation and OC, this study has several limitations. Firstly, the molecular mechanism by which HIC1 methylation is linked to the development of OC is still not fully understood. Secondly, the small number of studies limited the quality of meta-analysis and could affect the strength of the conclusion. The observed association could also be influenced by multiple confounding factors such as hormonal therapy, nulliparity, environmental factors and family history of OC. Finally, although no significant publication bias was found using the Begg's test and Egger's test, it is possible that negative and unpublished investigations may contribute some bias.
In conclusion, our analysis showed that HIC1 methylation was significantly associated with OC, thus providing a potential biomarker for the early diagnosis of OC, as well as a potential prognostic indicator. Further studies with sufficiently large sample size are needed to confirm the link between HIC1 methylation and OC before clinical application.

Author contributions
JG concepted and wrote an original draft. LFS concepted, supervised review and edited the draft. QQL participated in the experiment design and analysis. All authors contributed to editorial changes in the manuscript. All the authors read and approved the final manuscript.

Ethics approval and consent to participate
All subjects gave their informed consent for inclusion before they participated in the study. This study was approved by the Ethics Committee of Beijing Jinshuitan Hospital with approval number KW-288731.