Tabriz University of Medical Sciences Advanced Pharmaceutical Bulletin 2228-5881 16 1 2026 05 19 GAS2 Co-Expression Networks in Breast Cancer: Identification of Potential Biomarkers and Therapeutic Targets 129 138 10.34172/apb.025.46055 EN Samin Rahimi https://orcid.org/0000-0002-3081-6583 Mehdi Haghi https://orcid.org/0000-0001-8400-4209 Dariush Najarzadeh https://orcid.org/0000-0003-4214-3969 Mohammad Ali Hosseinpour Feizi https://orcid.org/0000-0002-1508-5022 Journal Article 10.34172/apb.025.46055 2025 07 20 2025 10 27 Introduction: Breast Cancer (BCa) remains the leading cause of cancer-related mortality among women, underscoring the need for developing more effective novel biomarkers. This study investigated the role of Growth Arrest-Specific 2 (GAS2) and its co-expressed genes in breast cancer. Methods: RNA-Seq data from 60 matched normal and malignant breast tissue samples (GSE183947) were analyzed. Expression values were normalized using FPKM, and GAS2 co-expression networks were constructed with SUM Lasso and linear regression. Gene-gene interaction networks were examined using Gephi software. Results: GAS2 expression was significantly reduced in tumors compared with normal tissues (P<0.01). Distinct sets of GAS2-associated genes were identified in cancer versus normal tissues, with tumor-associated partners (TAS2R14, PHF21B, CNTN5, UGT2B15) linked to drug metabolism and signaling, and normal-associated partners (DCC, STAT5A, ZCRB1) linked to transcriptional and cytoskeletal regulation. Network analysis revealed substantial differences in gene expression patterns between tumor and normal tissues, indicating GAS2’s involvement in cancer-specific signaling pathways. Conclusion: GAS2 displays context-dependent gene interactions and reduced expression in BCa, suggesting potential relevance to tumor biology. While these findings support its value as a candidate biomarker, experimental validation is required before translational applications can be established.