An evaluation of gastric adenocarcinoma-associated CircRNAs based on microarray meta-analysis and ceRNA networks Article Swipe
Liora Yesharim
,
Saeed Talebi
,
Marzieh Mojbafan
,
Mahdi Alemrajabi
,
Shahram Teimourian
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.tranon.2022.101611
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.tranon.2022.101611
Gastric cancer is the fourth leading cause of cancer-related mortality and one of the most commonly diagnosed malignancies worldwide. Gastric adenocarcinoma (GAC) accounts for the majority of gastric cancer cases. Circular RNAs (circRNAs) have been shown to be associated with carcinogenesis and cancer progression. This research aims to investigate GAC-associated circRNAs and the underlying mechanisms of circRNA-miRNA-mRNA networks in the development and progression of GAC. Differentially expressed miRNAs and mRNAs (DEMs and DEGs) were identified in Gene Expression Omnibus (GEO) microarray datasets using the R package Limma. A microarray meta-analysis was performed to identify potential GAC-associated circRNAs with high statistical power, resulting in 13 up-regulated and 19 down-regulated circRNAs. CircRNA-miRNA-mRNA networks were constructed by combining predicted and experimentally validated databases and considering differentially expressed miRNAs and mRNAs. The constructed ceRNA networks revealed the potential regulatory effect of hsa_circ_0002019 and hsa_circ_0074736 on key survival-related genes. The expression levels of these two circRNAs were measured in plasma samples from GAC patients and healthy controls using SYBR Green-based real-time PCR. Axon guidance, cellular senescence, AGE-RAGE signaling pathway in diabetic complications, and AMPK signaling pathway were among the major significant (P-value <0.05) enriched pathways of "main mRNAs" in the constructed ceRNA networks. In conclusion, we identified strongly correlated circRNAs and their likely mechanisms of action in GAC, which may improve the knowledge of regulatory networks underlying GAC formation and contribute to developing better strategies for early diagnosis, prognosis, and treatment.
Related Topics
Concepts
Competing endogenous RNA
microRNA
Biology
Microarray
Cancer
Microarray analysis techniques
Computational biology
Gene
Carcinogenesis
Bioinformatics
Circular RNA
Gene expression
Cancer research
Long non-coding RNA
Genetics
RNA
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.tranon.2022.101611
- OA Status
- gold
- Cited By
- 5
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4313379682
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4313379682Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.tranon.2022.101611Digital Object Identifier
- Title
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An evaluation of gastric adenocarcinoma-associated CircRNAs based on microarray meta-analysis and ceRNA networksWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-29Full publication date if available
- Authors
-
Liora Yesharim, Saeed Talebi, Marzieh Mojbafan, Mahdi Alemrajabi, Shahram TeimourianList of authors in order
- Landing page
-
https://doi.org/10.1016/j.tranon.2022.101611Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.tranon.2022.101611Direct OA link when available
- Concepts
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Competing endogenous RNA, microRNA, Biology, Microarray, Cancer, Microarray analysis techniques, Computational biology, Gene, Carcinogenesis, Bioinformatics, Circular RNA, Gene expression, Cancer research, Long non-coding RNA, Genetics, RNATop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
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2024: 3, 2023: 2Per-year citation counts (last 5 years)
- References (count)
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42Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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