RNF43 p.G659fs 通过 PI3K/AKT/mTOR 信号通路和 HLA-E 上调导致 MSI-high 结直肠癌中 NK 细胞功能障碍
RNF43 p.G659fs leads to natural killer cell dysfunction in MSI-high colorectal cancer through PI3K/AKT/mTOR signaling and HLA-E up-regulation.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:C-C Motif Chemokine Ligand 5 (CCL5): A Potential Biomarker and Immunotherapy Target for Osteosarcoma.
C-C Motif Chemokine Ligand 5 (CCL5): A Potential Biomarker and Immunotherapy Target for Osteosarcoma.
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我们发现 CCL5 可作为骨肉瘤的早期诊断基因,且 CCL5 与免疫细胞相互作用,影响肿瘤的发生发展。这些发现对骨肉瘤的早期检测及新治疗靶点的识别具有重要意义。
骨肉瘤(OS)是骨组织最常见的原发性恶性肿瘤,其起病隐匿,早期难以发现,且缺乏高特异性和高敏感性的早期诊断标志物。因此,本研究旨在识别有助于早期诊断OS并改善患者预后的潜在生物标志物。
将GSE12789、GSE28424、GSE33382和GSE36001数据集合并并标准化,以识别差异表达基因(DEGs)。通过基因本体(GO)、京都基因与基因组百科全书(KEGG)和疾病本体(DO)对数据进行分析。基于应用两种回归方法获得的共同DEG选择枢纽基因:最小绝对收缩和选择算子(LASSO)和支持向量机(SVM)。然后在GSE42572数据集中评估枢纽基因的诊断价值。最后,通过CIBERSORT分析免疫细胞浸润与关键基因之间的相关性。
LASSO和SVM的回归分析结果得到以下三个DEG:FK501结合蛋白51(FKBP5)、C-C基序趋化因子配体5(CCL5)、补体成分1 Q亚成分B链(C1QB)。我们使用受试者工作特征(ROC)分析评估了三种生物标志物(FKBP5、CCL5和C1QB)对骨肉瘤的诊断性能。在训练组中,FKBP5、CCL5和C1QB的曲线下面积(AUC)分别为0.907、0.874和0.676。在验证组中,FKBP5、CCL5和C1QB的AUC分别为0.618、0.932和0.895。值得注意的是,通过多种免疫细胞类型,如浆细胞、CD8+ T细胞、T调节细胞(Tregs)、活化NK细胞、活化树突状细胞和活化肥大细胞,这些基因在肿瘤组织中的表达高于正常组织。这些免疫细胞类型也与我们所鉴定的三个诊断基因的表达水平相关。
Osteosarcoma (OS) is the most common primary malignant tumor of bone tissue, which has an insidious onset and is difficult to detect early, and few early diagnostic markers with high specificity and sensitivity. Therefore, this study aims to identify potential biomarkers that can help diagnose OS in its early stages and improve the prognosis of patients.
The data sets of GSE12789, GSE28424, GSE33382 and GSE36001 were combined and normalized to identify Differentially Expressed Genes (DEGs). The data were analyzed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG) and Disease Ontology (DO). The hub gene was selected based on the common DEG that was obtained by applying two regression methods: the Least Absolute Shrinkage and Selection Operator (LASSO) and Support vVector Machine (SVM). Then the diagnostic value of the hub gene was evaluated in the GSE42572 data set. Finally, the correlation between immunocyte infiltration and key genes was analyzed by CIBERSORT.
The regression analysis results of LASSO and SVM are the following three DEGs: FK501 binding protein 51 (FKBP5), C-C motif chemokine ligand 5 (CCL5), complement component 1 Q subcomponent B chain (C1QB). We evaluated the diagnostic performance of three biomarkers (FKBP5, CCL5 and C1QB) for osteosarcoma using receiver operating characteristic (ROC) analysis. In the training group, the area under the curve (AUC) of FKBP5, CCL5 and C1QB was 0.907, 0.874 and 0.676, respectively. In the validation group, the AUC of FKBP5, CCL5 and C1QB was 0.618, 0.932 and 0.895, respectively. It is noteworthy that these genes were more expressed in tumor tissues than in normal tissues by various immune cell types, such as plasma cells, CD8+ T cells, T regulatory cells (Tregs), activated NK cells, activated dendritic cells and activated mast cells. These immune cell types are also associated with the expression levels of the three diagnostic genes that we identified.
We found that CCL5 can be considered an early diagnostic gene of osteosarcoma, and CCL5 interacts with immune cells to influence tumor occurrence and development. These findings have important implications for the early detection of osteosarcoma and the identification of novel therapeutic targets.
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