Personalized Treatment of Advanced Gastric Cancer Guided by the MiniPDX Model

医学 癌症 药品 养生 化疗 抗药性 肿瘤科 内科学 个性化医疗 药理学 生物信息学 生物 微生物学
作者
Jianzheng Wang,Jinxi Huang,Hui Wang,Wei Yang,Qiwen Bai,Zhentao Yao,Qingli Li,Huifang Lv,Beibei Chen,Caiyun Nie,Weifeng Xu,Shuiping Tu,Hongle Li,Xiaobing Chen
出处
期刊:Journal of Oncology [Hindawi Limited]
卷期号:2022: 1-11 被引量:9
标识
DOI:10.1155/2022/1987705
摘要

Background. The morbidity and mortality of gastric cancer are high in China. There are challenges to develop precise and individualized drug regimens for patients with gastric cancer after a standard treatment. Choosing the most appropriate anticancer drug after a patient developing drug resistance is very important to improve the patient’s prognosis. MiniPDX has been widely used as a new and reliable preclinical research model to predict the sensitivity of anticancer drugs. Methods. The OncoVee® MiniPDX system developed by Shanghai LIDE Biotech Co., Ltd. was used to establish the MiniPDX models using specimens of patients with gastric cancer. The cancer tissues were biopsied under endoscopy, and then, the tumor cell suspension was prepared for a drug sensitivity test by subcutaneously implanting into Balb/c-nude mice. The selected optimal regimen obtained from the MiniPDX assay was used to treat patients with drug-resistant gastric cancer. Results. We successfully established an individualized and sensitive drug screening system for four patients from January 2021 to July 2021. MiniPDX models identified potentially effective drugs for these four patients, with partial remission in two of the patients after treatment and disease progression in the remaining of two patients. Severe side effects from chemotherapy or targeted therapy were not observed in all patients. Conclusion. Establishing a personalized drug screening system for patients with drug-resistant gastric cancer can guide the selection of clinical drugs, improve the clinical benefit of patients, and avoid ineffective treatments. It can be an effective supplement for treatment options.
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