Evidence map›Paper›PMID 42016026›Full record

ArticleInternational journal of molecular and cellular medicine2025

Integrated Bioinformatics and Experimental Validation of the hsa_circ_0000378/miR-205-5p/RAD51 ceRNA Axis in Breast Cancer.

Ali Abbasi, Nahid Nafisi, Pejman Morovat, Mitra Nourbakhsh, Mehdi Sepidarkish, Mohamadreza Ahmadifard, Arash M Ashrafi, Mehdi Pouramir

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Article in International journal of molecular and cellular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ali AbbasiStudent Research Committee, Babol University of Medical Sciences, Babol, Iran.
Nahid NafisiSurgery Department, Rasoul Akram Hospital Clinical Research Development Center (RCRDC), Iran University of Medical Sciences, Tehran, Iran.
Pejman MorovatDepartment of Medical Biotechnology, Faculty of Medicine, Babol University of Medical Sciences, Babol, Iran.
Mitra NourbakhshDepartment of Biochemistry, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Mehdi SepidarkishDepartment of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran.
Mohamadreza AhmadifardDepartment of Medical Genetics and Molecular Biology, Faculty of Medicine, Babol University of Medical Sciences, Babol, Iran.
Arash M AshrafiCellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
Mehdi PouramirStudent Research Committee, Babol University of Medical Sciences, Babol, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) remains the leading cause of cancer-related mortality in women worldwide, primarily due to its high invasiveness and therapeutic resistance. This study explores the role of noncoding RNAs, circular RNAs (circRNAs), in BC progression through a competing endogenous RNA (ceRNA) network. Three GEO circRNA microarray datasets (GSE101123, GSE165884, GSE182471) were retrieved, normalized, and batch-corrected using ComBat. Differentially expressed circRNAs (DEcircRNAs) were identified via limma (|log₂FC| > 1, FDR < 0.05). Differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEgenes) were derived from TCGA-BRCA RNA-Seq (1,091 tumors, 113 normals) and miRNA-Seq (1,078 tumors, 104 normals) data using DESeq2 (|log₂FC| > 1, FDR < 0.05). CircRNAs harboring miRNA response elements (MREs) were selected via CSCD, and miRNA-mRNA interactions predicted through TarBase, prioritizing upregulated DEgenes. A ceRNA network was constructed in Cytoscape based on expression concordance. The hsa_circ_0000378/hsa-miR-205-5p/RAD51 axis was validated in 48 paired BC and adjacent non-tumor tissues by RT-qPCR. Results indicated hsa_circ_0000378 upregulation (2.74-fold, p<0.001), hsa-miR-205-5p downregulation (0.64-fold, p=0.0022), and RAD51 upregulation (3.46-fold, p<0.001) in tumors. Spearman correlations showed negative associations between hsa_circ_0000378 and hsa-miR-205-5p (r = -0.474, p<0.001), hsa-miR-205-5p and RAD51 (r = -0.383, p<0.001), and positive between hsa_circ_0000378 and RAD51 (r = 0.497, p<0.001), supporting ceRNA regulation. ROC analysis revealed RAD51's diagnostic potential (AUC=0.83, 95% CI: 0.74-0.90, sensitivity=0.81, specificity=0.55), followed by hsa_circ_0000378 (AUC=0.75, 95% CI: 0.65-0.85, sensitivity=0.71, specificity=0.77), and hsa-miR-205-5p (AUC=0.66, 95% CI: 0.56-0.76, sensitivity=0.69, specificity=0.55). These results propose the hsa_circ_0000378/hsa_miR-205-5p/RAD51 axis as a potential biomarker; mechanistic validation and larger cohorts are needed for clinical application.

Indexed as

BioinformaticBreast CancerceRNA networkCircular RNAMicro RNARAD51Real-Time PCR

Identifiers

PMID42016026
PMCPMC13092840

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.