Zhong Yujian, Gao Bohua, Tong Kai, Li Lan, Wei Qingjun, Hu Yong
Department of Orthopedics, Renmin Hospital of Wuhan University, No. 99 Zhangzhidong Road, Wuchang District, Wuhan, 430060, China.
Department of Orthopedics Trauma, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, 570311, Hainan, China.
Sci Rep. 2025 May 15;15(1):16859. doi: 10.1038/s41598-025-99419-5.
The centrosome, a vital component in mitosis in eukaryotes, plays a pivotal role in cancer progression by influencing the proliferation and differentiation of malignant cells, making it a significant therapeutic target. We collected genes associated with centrosomes from existing literature and established a prognostic model for 85 osteosarcoma patients from the TARGET database. Genes associated with prognosis were identified through univariate Cox regression. We then mitigated overfitting by addressing collinearity using LASSO regression. Ultimately, a set of five genes was selected for the model through multivariable Cox regression. Model performance was assessed using ROC curves, which yielded a training set AUC of 0.965 and a validation set AUC of 0.770, indicating satisfactory model performance. We further identified genes with differential expression in high and low-risk groups and conducted functional enrichment analysis using KEGG, GO, Progeny, GSVA, and GSEA. Results revealed significant variances in various immune-related pathways between high and low-risk cohorts. Analysis of the immune microenvironment using ssGSEA and ESTIMATE indicated that individuals with unfavorable prognoses had lower immune scores, stromal scores, and ESTIMATE scores, coupled with higher tumor purity. This suggests that high-risk individuals have compromised immune microenvironments, potentially contributing to their unfavorable prognoses. Additionally, drug sensitivity and molecular docking analysis revealed increased responsiveness to paclitaxel in high-risk individuals, implying its prognostic value. The JTB-encoded protein exhibited a negative binding energy of - 5.5 kcal/mol when interacting with paclitaxel, indicating its potential to enhance the patient's immune microenvironment. This framework enables patient prognosis prediction and sheds light on paclitaxel's mechanism in osteosarcoma treatment, facilitating personalized treatment approaches.
中心体是真核生物有丝分裂中的重要组成部分,通过影响恶性细胞的增殖和分化在癌症进展中起关键作用,使其成为一个重要的治疗靶点。我们从现有文献中收集了与中心体相关的基因,并为来自TARGET数据库的85例骨肉瘤患者建立了一个预后模型。通过单变量Cox回归确定与预后相关的基因。然后,我们使用LASSO回归解决共线性问题来减轻过拟合。最终,通过多变量Cox回归为该模型选择了一组五个基因。使用ROC曲线评估模型性能,训练集AUC为0.965,验证集AUC为0.770,表明模型性能令人满意。我们进一步鉴定了高风险和低风险组中差异表达的基因,并使用KEGG、GO、Progeny、GSVA和GSEA进行功能富集分析。结果显示,高风险和低风险队列之间在各种免疫相关途径中存在显著差异。使用ssGSEA和ESTIMATE对免疫微环境进行分析表明,预后不良的个体免疫评分、基质评分和ESTIMATE评分较低,同时肿瘤纯度较高。这表明高风险个体的免疫微环境受损,可能导致其预后不良。此外,药物敏感性和分子对接分析显示,高风险个体对紫杉醇的反应性增加,这意味着其具有预后价值。JTB编码的蛋白质在与紫杉醇相互作用时表现出-5.5千卡/摩尔的负结合能,表明其具有增强患者免疫微环境的潜力。该框架能够预测患者预后,并阐明紫杉醇在骨肉瘤治疗中的作用机制,促进个性化治疗方法的发展。