基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Integrated Transcriptomic Analysis Identifies Overlapping Gene Networks Between Breast Cancer Stem Cells and Paclitaxel-Primed Mesenchymal Stem Cell-Activated T Cells as Potential Immunotherapeutic Targets.
Integrated Transcriptomic Analysis Identifies Overlapping Gene Networks Between Breast Cancer Stem Cells and Paclitaxel-Primed Mesenchymal Stem Cell-Activated T Cells as Potential Immunotherapeutic Targets.
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本研究揭示了连接 BCSCs 与免疫激活的关键分子网络,确定 TP53、AKT1 和 STAT3 为核心治疗靶点。紫杉醇预处理的 MSC 激活 T 细胞通过调控 TP53 和 PIK3CA 通路与化疗协同抑制 BCSC 活力,为乳腺癌联合免疫治疗提供了机制依据。
乳腺癌干细胞(BCSCs)是化疗耐药、转移和肿瘤复发的原因。紫杉醇预处理的间充质干细胞(MSCs)能够激活T细胞,提供了一种新的免疫治疗途径。然而,BCSC与免疫相互作用的分子机制仍知之甚少。
识别BCSCs、紫杉醇处理细胞、活化T细胞和紫杉醇预处理MSCs之间重叠的基因网络,并验证其在靶向BCSCs中的功能相关性。
采用TCGA数据进行比较转录组分析,以鉴定在BCSCs、紫杉醇处理细胞、活化T细胞和MSCs之间共表达的基因。使用STRING-DB、DAVID和cBioPortal进行蛋白质-蛋白质相互作用网络分析、基因本体(GO)富集和KEGG通路映射。在151例乳腺癌样本中评估了突变分析和生存相关性。使用MTT活力测定和qRT-PCR在转移性乳腺癌细胞中进行实验验证,这些细胞用紫杉醇、活化T细胞条件培养基和MSC衍生因子处理。
我们鉴定出158个在四种条件下共表达的基因,形成一个高度互联的PPI网络(136个节点,524条边)。网络中心性分析显示TP53、AKT1和STAT3为顶级枢纽基因。GO富集分析表明其显著参与上皮细胞增殖、应激反应和转录调控。KEGG通路分析显示富集于PI3K-Akt信号通路、PD-L1/PD-1检查点通路和Th1/Th2分化。TP53是最常见的突变基因(77.5%),与不良预后相关。实验验证表明,紫杉醇联合活化T细胞治疗使BCSC活力降低75%,上调TP53表达,并将PIK3CA表达抑制85%。
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.
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.
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.
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%.
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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