Cargando…

OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis

Background: The association of opioid binding protein cell adhesion molecule-like (OPCML) gene methylation with ovarian cancer risk remains unclear. Methods: We identified eligible studies by searching the PubMed, Web of Science, ScienceDirect, and Wanfang databases. Odds ratios (ORs) and 95% confid...

Descripción completa

Detalles Bibliográficos
Autores principales: Shao, Yang, Kong, Jing, Xu, Hanzi, Wu, Xiaoli, Cao, YuePeng, Li, Weijian, Han, Jing, Li, Dake, Xie, Kaipeng, Wu, Jiangping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990783/
https://www.ncbi.nlm.nih.gov/pubmed/33777925
http://dx.doi.org/10.3389/fcell.2021.570898
_version_ 1783669121247870976
author Shao, Yang
Kong, Jing
Xu, Hanzi
Wu, Xiaoli
Cao, YuePeng
Li, Weijian
Han, Jing
Li, Dake
Xie, Kaipeng
Wu, Jiangping
author_facet Shao, Yang
Kong, Jing
Xu, Hanzi
Wu, Xiaoli
Cao, YuePeng
Li, Weijian
Han, Jing
Li, Dake
Xie, Kaipeng
Wu, Jiangping
author_sort Shao, Yang
collection PubMed
description Background: The association of opioid binding protein cell adhesion molecule-like (OPCML) gene methylation with ovarian cancer risk remains unclear. Methods: We identified eligible studies by searching the PubMed, Web of Science, ScienceDirect, and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to determine the association of OPCML methylation with ovarian cancer risk. Meta-regression and subgroup analysis were used to assess the sources of heterogeneity. Additionally, we analyzed the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets to validate our findings. Results: Our study included 476 ovarian cancer patients and 385 controls from eight eligible studies. The pooled OR was 33.47 (95% CI = 12.43–90.16) in the cancer group vs. the control group under the random-effects model. The association was still significant in subgroups according to sample type, control type, methods, and sample sizes (all P < 0.05). Sensitivity analysis showed that the finding was robust. No publication bias was observed in Begg's (P = 0.458) and Egger's tests (P = 0.261). We further found that OPCML methylation was related to III/IV (OR = 4.20, 95% CI = 1.59–11.14) and poorly differentiated grade (OR = 4.37; 95% CI = 1.14–16.78). Based on GSE146552 and GSE155760, we validated that three CpG sites (cg16639665, cg23236270, cg15964611) in OPCML promoter region were significantly higher in cancer tissues compared to normal tissues. However, we did not observe the associations of OPCML methylation with clinicopathological parameters and overall survival based on TCGA ovarian cancer data. Conclusion: Our findings support that OPCML methylation is associated with an increased risk of ovarian cancer.
format Online
Article
Text
id pubmed-7990783
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-79907832021-03-26 OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis Shao, Yang Kong, Jing Xu, Hanzi Wu, Xiaoli Cao, YuePeng Li, Weijian Han, Jing Li, Dake Xie, Kaipeng Wu, Jiangping Front Cell Dev Biol Cell and Developmental Biology Background: The association of opioid binding protein cell adhesion molecule-like (OPCML) gene methylation with ovarian cancer risk remains unclear. Methods: We identified eligible studies by searching the PubMed, Web of Science, ScienceDirect, and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to determine the association of OPCML methylation with ovarian cancer risk. Meta-regression and subgroup analysis were used to assess the sources of heterogeneity. Additionally, we analyzed the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets to validate our findings. Results: Our study included 476 ovarian cancer patients and 385 controls from eight eligible studies. The pooled OR was 33.47 (95% CI = 12.43–90.16) in the cancer group vs. the control group under the random-effects model. The association was still significant in subgroups according to sample type, control type, methods, and sample sizes (all P < 0.05). Sensitivity analysis showed that the finding was robust. No publication bias was observed in Begg's (P = 0.458) and Egger's tests (P = 0.261). We further found that OPCML methylation was related to III/IV (OR = 4.20, 95% CI = 1.59–11.14) and poorly differentiated grade (OR = 4.37; 95% CI = 1.14–16.78). Based on GSE146552 and GSE155760, we validated that three CpG sites (cg16639665, cg23236270, cg15964611) in OPCML promoter region were significantly higher in cancer tissues compared to normal tissues. However, we did not observe the associations of OPCML methylation with clinicopathological parameters and overall survival based on TCGA ovarian cancer data. Conclusion: Our findings support that OPCML methylation is associated with an increased risk of ovarian cancer. Frontiers Media S.A. 2021-03-11 /pmc/articles/PMC7990783/ /pubmed/33777925 http://dx.doi.org/10.3389/fcell.2021.570898 Text en Copyright © 2021 Shao, Kong, Xu, Wu, Cao, Li, Han, Li, Xie and Wu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Shao, Yang
Kong, Jing
Xu, Hanzi
Wu, Xiaoli
Cao, YuePeng
Li, Weijian
Han, Jing
Li, Dake
Xie, Kaipeng
Wu, Jiangping
OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title_full OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title_fullStr OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title_full_unstemmed OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title_short OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis
title_sort opcml methylation and the risk of ovarian cancer: a meta and bioinformatics analysis
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990783/
https://www.ncbi.nlm.nih.gov/pubmed/33777925
http://dx.doi.org/10.3389/fcell.2021.570898
work_keys_str_mv AT shaoyang opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT kongjing opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT xuhanzi opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT wuxiaoli opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT caoyuepeng opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT liweijian opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT hanjing opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT lidake opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT xiekaipeng opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis
AT wujiangping opcmlmethylationandtheriskofovariancancerametaandbioinformaticsanalysis