A Multicentre Clinical Study of Sarcoma Personalised Treatment Using Patient-Derived Tumour Xenografts

医学 一致性 肿瘤科 肉瘤 内科学 活检 疾病 病理
作者
Hongyan Xu,Hui Zheng,Q Zhang,Hang Song,Q. Wang,Jianru Xiao,Yang Dong,Zhiyong Shen,Shaohe Wang,Shuhong Wu,Yuang Wei,Weiqi Lu,Yueyong Zhu,Xiaohui Niu
出处
期刊:Clinical Oncology [Elsevier BV]
卷期号:35 (1): e48-e59 被引量:7
标识
DOI:10.1016/j.clon.2022.06.002
摘要

Aims Medication for advanced sarcomas has not improved for three decades. Patient-derived tumour xenografts (PDTX) are a promising solution for developing new therapies and real-time personalised medicine because of their highly effective prediction of drug efficacy. However, there is a dearth of PDTX models for sarcomas due to the scarcity and heterogeneity of the disease. Materials and methods A multicentre clinical collaborative study (ChiCTR–OOC–17013617) was carried out. Fresh patient tumour tissues via resection or biopsy were used for the PDTX set-up. The standard medical care chosen by the physician was given to the patient, in parallel with testing on multiple regimens. The outcomes of patients' responses and PDTX tests were compared. Comprehensive analyses were carried out to assess the clinical value of PDTX for the treatment of sarcomas. Living tissues from successfully engrafted cases were deposited into a repository. Results Forty-two cases, including 36 bone sarcomas and six soft-tissue sarcomas, were enrolled; the overall engraftment rate was 73.8%. Histopathological examination showed a 100% consistency between primary tumours and tumour grafts. The engraftment rate was independent of age, gender and sampling methods, but was associated with subtypes of tumour. The outgrowth time of tumour grafts could be associated with prognosis. Major somatic mutations in tumour grafts occurred primarily in common tumour driver genes. Poor prognosis was associated with the KMT2C mutation. A drug efficacy test showed complete concordance between the PDTX model and patients' responses in 17 regimens. Conclusion PDTX is an ideal preclinical model for sarcomas because of its faithful preservation of the heterogeneity of the disease, a satisfactory engraftment rate and high accuracy in its prediction of drug efficacy.
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