Haoran Mu1, Dongqing Zuo1, Jie Chen2, Zhigang Liu3, Zhuo Wang3, Liu Yang1, Qihui Shi3,4,5, Yingqi Hua1. 1. Shanghai Bone Tumor Institute and Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China. 2. Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China. 3. Shanghai Key Laboratory of Medical Epigenetics and the International Co-laboratory of Medical Epigenetics and Metabolism (MOST), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China. 4. Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer (SMHC) and Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai 201199, China. 5. Shanghai Engineering Research Center of Biomedical Analysis Reagents, Shanghai 201203, China.
Abstract
OBJECTIVE: Osteosarcoma (OS) is an aggressive, highly metastatic, relatively drug-resistant bone tumor with poor long-term survival rates. The presence and persistence of circulating tumor cells (CTCs) in the peripheral blood are believed to be associated with treatment inefficiency and distant metastases. A blood-based CTC test is thus greatly needed for monitoring disease progression and predicting clinical outcomes. However, traditional methods cannot detect CTCs from tumors of mesenchymal origin such as OS, and research on CTC detection in mesenchymal tumors has been hindered for years. METHODS: In this study, we developed a CTC test based on hexokinase 2, a metabolic function-associated marker, for the detection and surveillance of OS CTCs, and subsequently explored its clinical value. Twelve patients with OS were enrolled as the training cohort for serial CTC tests. Dynamic CTC counting, in combination with therapy evaluation and post-treatment follow-up, was used to establish a model for predicting post-chemotherapy evaluation and disease-free survival, and the model was further validated with a cohort of 8 patients with OS. RESULTS: Two dynamic CTC number patterns were identified, and the resulting predictive model exhibited 92% consistency with the clinical outcomes. This model suggested that a single CTC test has similar predictive power to serial CTC analysis. In the validation cohort, the single CTC test exhibited 100% and 87.5% consistency with therapy response and disease-free survival, respectively. CONCLUSIONS: Our non-invasive test for detection and surveillance of CTCs enables accurate prediction of therapy efficiency and prognosis, and may be clinically valuable for avoiding inefficient therapy and prolonging survival.
OBJECTIVE: Osteosarcoma (OS) is an aggressive, highly metastatic, relatively drug-resistant bone tumor with poor long-term survival rates. The presence and persistence of circulating tumor cells (CTCs) in the peripheral blood are believed to be associated with treatment inefficiency and distant metastases. A blood-based CTC test is thus greatly needed for monitoring disease progression and predicting clinical outcomes. However, traditional methods cannot detect CTCs from tumors of mesenchymal origin such as OS, and research on CTC detection in mesenchymal tumors has been hindered for years. METHODS: In this study, we developed a CTC test based on hexokinase 2, a metabolic function-associated marker, for the detection and surveillance of OS CTCs, and subsequently explored its clinical value. Twelve patients with OS were enrolled as the training cohort for serial CTC tests. Dynamic CTC counting, in combination with therapy evaluation and post-treatment follow-up, was used to establish a model for predicting post-chemotherapy evaluation and disease-free survival, and the model was further validated with a cohort of 8 patients with OS. RESULTS: Two dynamic CTC number patterns were identified, and the resulting predictive model exhibited 92% consistency with the clinical outcomes. This model suggested that a single CTC test has similar predictive power to serial CTC analysis. In the validation cohort, the single CTC test exhibited 100% and 87.5% consistency with therapy response and disease-free survival, respectively. CONCLUSIONS: Our non-invasive test for detection and surveillance of CTCs enables accurate prediction of therapy efficiency and prognosis, and may be clinically valuable for avoiding inefficient therapy and prolonging survival.
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