Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel
Abstract 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...
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Nature Portfolio
2025-05-01
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| Online Access: | https://doi.org/10.1038/s41598-025-99419-5 |
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| author | Yujian Zhong Bohua Gao Kai Tong Lan Li Qingjun Wei Yong Hu |
| author_facet | Yujian Zhong Bohua Gao Kai Tong Lan Li Qingjun Wei Yong Hu |
| author_sort | Yujian Zhong |
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| description | Abstract 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. |
| format | Article |
| id | doaj-art-7f4adb2eaec148a2b00b3e9d754242d3 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-7f4adb2eaec148a2b00b3e9d754242d32025-08-20T01:51:27ZengNature PortfolioScientific Reports2045-23222025-05-0115111910.1038/s41598-025-99419-5Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxelYujian Zhong0Bohua Gao1Kai Tong2Lan Li3Qingjun Wei4Yong Hu5Department of Orthopedics, Renmin Hospital of Wuhan UniversityDepartment of Orthopedics Trauma, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University)Department of Orthopedics, Renmin Hospital of Wuhan UniversityDepartment of Orthopedics, Renmin Hospital of Wuhan UniversityDepartment of Orthopedics, The Second Affiliated Hospital of Guangxi Medical UniversityDepartment of Orthopedics, Renmin Hospital of Wuhan UniversityAbstract 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.https://doi.org/10.1038/s41598-025-99419-5OsteosarcomaCentrosomeTumor immune microenvironmentPrognostic modelIndividualized therapy |
| spellingShingle | Yujian Zhong Bohua Gao Kai Tong Lan Li Qingjun Wei Yong Hu Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel Scientific Reports Osteosarcoma Centrosome Tumor immune microenvironment Prognostic model Individualized therapy |
| title | Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel |
| title_full | Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel |
| title_fullStr | Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel |
| title_full_unstemmed | Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel |
| title_short | Constructing a prognostic model for osteosarcoma based on centrosome-related genes and identifying potential therapeutic targets of paclitaxel |
| title_sort | constructing a prognostic model for osteosarcoma based on centrosome related genes and identifying potential therapeutic targets of paclitaxel |
| topic | Osteosarcoma Centrosome Tumor immune microenvironment Prognostic model Individualized therapy |
| url | https://doi.org/10.1038/s41598-025-99419-5 |
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