Network-based meta-analysis and confirmation of genes ATP1A2, FXYD1, and ADCY3 associated with cAMP signaling in breast tumors compared to corresponding normal marginal tissues

Zahra Torki ¹, Davood Ghavi ², Zahra Foruzandeh ³

⁰Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. zahratorki94@gmail.com.

Cellular and Molecular Biology +

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December 21, 2024

View abstract on PubMed

Summary

This study identified gene expression signatures in breast cancer (BC) using meta-analysis. While bioinformatics suggested altered cAMP signaling, real-time PCR confirmed significant changes only for ATP1A2 in BC tissues.

Area Of Science

Oncology
Genomics
Bioinformatics

Background

Breast cancer (BC) is a heterogeneous disease with increasing global prevalence.
Understanding BC's molecular underpinnings requires identifying distinct gene expression signatures.
Transcriptome analysis and meta-analysis are crucial for uncovering commonalities across diverse BC datasets.

Purpose Of The Study

To identify common differentially expressed genes (DEGs) and signaling pathways in breast tumors using meta-analysis.
To validate key genes, particularly cAMP signaling pathway members, through bioinformatics and experimental methods.
To discover novel gene expression signatures and potential therapeutic targets for breast cancer.

Main Methods

Meta-analysis of five gene expression datasets (GSE70947, GSE70905, GSE10780, GSE29044, GSE42568) from breast tumor and normal tissues.
Identification of DEGs, hub genes, and pathway enrichment analysis (Gene Ontology, KEGG) using Network Analyst and EnrichR.
Validation of hub genes (ATP1A2, FXYD1, ADCY3) using Kaplan-Meier plotter, UALCAN, and Real-time PCR on patient samples.

Main Results

Meta-analysis identified 710 DEGs (392 overexpressed, 318 underexpressed) in breast tumors compared to normal tissues.
Upregulated pathways included progesterone-mediated oocyte maturation and NF-kappa B signaling; downregulated pathways included cancer-related and cAMP signaling.
Real-time PCR validation showed contradictory results to bioinformatics predictions for ATP1A2, FXYD1, and ADCY3, with only ATP1A2 exhibiting statistically significant differential expression.

Conclusions

Meta-analysis successfully identified BC-specific gene expression signatures and highlighted the cAMP signaling pathway's potential role.
Experimental validation revealed complex expression patterns for selected cAMP pathway members, underscoring the need for integrated analysis.
The study provides valuable insights into BC's molecular mechanisms, identifying ATP1A2 as a potential biomarker and therapeutic target.