Document Type : Research Articles
Authors
1
Oncology Surgery Department, Faculty of Medicine, Diponegoro University / Kariadi General Hospital, Semarang, Indonesia.
2
Department of Surgery, Faculty of Medicine, Universitas Sumatera Utara, Medan, Indonesia.
3
Department of Pharmaceutical Sciences, Faculty of Pharmacy, Universitas Airlangga, 60115 Surabaya, East Java, Indonesia.
4
Drug Development Research Group, Faculty of Pharmacy, Universitas Airlangga, Surabaya, 60115, East Java, Indonesia.
5
Department of Pharmaceutical Sciences, Faculty of Medicine, Universitas Negeri Semarang, Semarang, Indonesia.
Abstract
Background: Breast cancer stem cells (BCSCs) are responsible for chemotherapy resistance, metastasis, and tumor recurrence. Paclitaxel-primed mesenchymal stem cells (MSCs) can activate T cells, offering a novel immunotherapeutic approach. However, the molecular mechanisms underlying BCSC-immune interactions remain poorly understood. Objective: To identify overlapping gene networks between BCSCs, paclitaxel-treated cells, activated T cells, and paclitaxel-primed MSCs, and to validate their functional relevance in targeting BCSCs. Methods: Comparative transcriptomic analysis was performed using data from TCGA to identify genes co-expressed across BCSCs, paclitaxel-treated cells, activated T cells, and MSCs. Protein-protein interaction network analysis, Gene Ontology (GO) enrichment, and KEGG pathway mapping were conducted using STRING-DB, DAVID, and cBioPortal. Mutation analysis and survival correlations were assessed across 151 breast cancer samples. Experimental validation was performed using MTT viability assays and qRT-PCR in metastatic breast cancer cells treated with paclitaxel, activated T cell-conditioned medium, and MSC-derived factors. Results: We identified 158 genes co-expressed across all four conditions, forming a highly interconnected PPI network (136 nodes, 524 edges). Network centrality analysis revealed TP53, AKT1, and STAT3 as top hub genes. GO enrichment analysis demonstrated significant involvement in epithelial cell proliferation, stress responses, and transcriptional regulation. KEGG pathway analysis revealed enrichment in the PI3K-Akt signaling pathway, the PD-L1/PD-1 checkpoint pathway, and Th1/Th2 differentiation. TP53 was the most frequently mutated gene (77.5%), which correlated with a poor prognosis. Experimental validation demonstrated that combined paclitaxel and activated T cell treatment reduced BCSC viability by 75%, upregulated TP53 expression, and suppressed PIK3CA expression by 85%. Conclusion: This study reveals critical molecular networks connecting BCSCs and immune activation, identifying TP53, AKT1, and STAT3 as central therapeutic targets. Paclitaxel-primed MSC-activated T cells synergize with chemotherapy to suppress BCSC viability by modulating the TP53 and PIK3CA pathways, providing a mechanistic rationale for combinatorial immunotherapy in breast cancer.
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