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:Identification of Six N7-Methylguanosine-Related miRNA Signatures to Predict the Overall Survival and Immune Landscape of Triple-Negative Breast Cancer through In Silico Analysis.
Identification of Six N7-Methylguanosine-Related miRNA Signatures to Predict the Overall Survival and Immune Landscape of Triple-Negative Breast Cancer through In Silico Analysis.
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三阴性乳腺癌(TNBC)较为常见,死亡率可达25%。TNBC患者生存率较低,而N7-甲基鸟苷(m7G)修饰在TNBC中的意义尚不明确。
本研究通过计算机分析,探讨TNBC患者中与m7G相关的miRNA。研究人员从癌症基因组图谱(TCGA)数据库获取RNA测序和临床数据,并通过TargetScan预测靶向典型m7G修饰调节因子甲基转移酶样1(METTL1)和WD重复结构域4(WDR4)的miRNA。研究构建miRNA风险模型,使用R软件包评估其预后价值;通过单样本基因集富集分析评估免疫浸润,并进一步分析免疫检查点表达。最终筛选出miR-421、miR-5001-3p、miR-4326、miR-1915-3p、miR-3177-5p和miR-4505构建风险模型。由N分期和风险模型构成的列线图可有效预测TNBC患者总生存期。Treg和TIL与风险模型密切相关;高风险组中4种免疫检查点CD28、CTLA-4、ICOS和TNFRSF9表达更高。研究建立了由m7G相关miRNA组成的风险模型。该模型可能成为预后生物标志物,并为TNBC患者免疫治疗提供新的思路。
Triple-negative breast cancer (TNBC) is a widely prevalent breast cancer, with a mortality rate of up to 25%. TNBC has a lower survival rate, and the significance of N7-methylguanosine (m7G) modification in TNBC remains unclear.
Thus, this study is aimed at investigating m7G-related miRNAs in TNBC patients through in silico analysis. In our research, RNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. The miRNAs targeting typical m7G modification regulators Methyltransferase-like 1 (METTL1) and WD repeat domain 4 (WDR4) were predicted on the TargetScan website. A miRNA risk model was built, and its prognostic value was evaluated by R soft packages. Single-sample gene set enrichment analysis was used to assess immune infiltration, and further expression of immune checkpoints was investigated.
As a result, miR-421, miR-5001-3p, miR-4326, miR-1915-3p, miR-3177-5p, and miR-4505 were identified to create the risk model. A nomogram consisting of the stage N and risk model predicted overall survival effectively among TNBC patients.
Treg and TIL were shown to be strongly linked to the risk model, and the high-risk group had higher levels of four immune checkpoints expression (CD28, CTLA-4, ICOS, and TNFRSF9). A risk model consisting of m7G-related miRNAs was constructed. The findings of the current study could be used as a prognostic biomarker and can provide a novel immunotherapy insight for TNBC patients.
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