Peking University develops micro-tumor prediction model: accuracy of drug efficacy exceeds 90%, subject to large-scale verification

Reporter : He Liping

Publisher : The Paper, re-produced on ScienceNet

Ref : http://news.sciencenet.cn/htmlnews/2020/6/442141.shtm

Direct translation

Image : Cancer cells. Courtesy of Science Nordic

 

Despite the continuous advancement of medicine, it is still difficult to determine the best treatment plan for each cancer patient. Especially in recent years, as the concept of oncology precision medicine is put forward, tumor gene detection as the basis of oncology precision medicine has emerged, but the potential and effect of clinical application of genomics technology are also limited.

Recently, the research team of the Department of Biomedical Engineering, School of Engineering, Peking University, School of Mathematics, Peking University, Peking University Cancer Hospital, Peking University People’s Hospital and other research teams jointly published in the journal Science Translational Medicine (IF=17.2) A study titled "Patient-Derived Tumor-Like Cell Clusters for Drug Testing in Cancer Therapy". The research team has developed a new method for primary tumor cells to assemble their own waywardly to form micro-tumors, and establish micro-tumor models of breast cancer and other cancers. The clinical experiment results show that the accuracy of the micro-tumor model to predict the patient's drug efficacy is as high as 90%.

Corresponding authors of the study were Jianjian Zhong, a tenured professor in the Department of Biomedical Engineering, Peking University Institute of Technology, and Professor Ji Jiafu, dean of Peking University Cancer Hospital.

It is worth noting that there are currently many methods for analyzing the sensitivity of tumor drugs. Over the past 60 years, hundreds of models or methods of tumor susceptibility testing have been reported. Among them, tumor organoids (PDO) and patient-derived tumor xenograft models are more influential. However, these technologies have their shortcomings, such as limitations in terms of test cycle, accuracy, test drug flux, and test cost, so the prospects for guiding clinical medication are not clear.

The method designed and developed by the research team this time is called the patient-derived tumor-like cell cluster (patient-derived tumor-like cell cluster), through the self-assembly of primary epithelial cells, fibroblasts and immune cells and Proliferation reproduces the primary tumor in structure and function.

The research team believes that micro tumor PTC has obvious advantages in terms of culture time and cell composition. Whether it is a surgical sample or a puncture sample, 100-2000 drugs can be detected within 2 weeks; in addition, micro tumor PTC is composed of tumor stem cells, epithelial cells, fibroblasts, macrophages and other cells, which can be very good To reproduce the interaction of the tumor cell's multicellular microenvironment with tumor epithelial cells.

The research team analyzed by immunofluorescence, flow cytometry, transcriptome sequencing and other methods, which showed that the microtumor PTC and tumor tissue have a high degree of consistency in terms of molecules, cells and tissue structure.

The authors pointed out in the paper, "PTCs enable us to complete personalized drug testing within 2 weeks of obtaining tumor samples. The culture conditions and drug concentrations determined under the PTC model help its clinical application in precision oncology. "

It is worth mentioning that the team used the microtumor PTC drug sensitivity detection model for clinical double-blind verification. For the 35 breast cancer patients who were enrolled and obtained PTC, the clinical efficacy was evaluated using imaging combined with the Miller & Payne grading system. The coincidence rate of PTC test results and clinical efficacy reached 91.4%. The team also conducted a simultaneous verification of the pathological assessment, and the prediction rate for patients with chemotherapy ineffectiveness reached 87.5%, which is of great significance for the precise treatment of breast cancer patients.

The paper also shows that the study of 59 patients with gastric cancer, colorectal cancer, or breast cancer showed that the overall accuracy of predicting their clinical results was 93%. The research team used PTC to guide the chemotherapy of a patient with recurrent and metastatic colorectal mucinous adenocarcinoma after routine treatment. After three cycles of unconventional treatment determined by PTC, the patient showed a positive therapeutic effect.

The research team emphasized that these findings need to be validated in larger clinical trials, but they show that the PTC model can be prospectively applied to the choice of clinical treatment decisions.

The official website of Peking University People's Hospital also mentioned in the report on the results, "Currently, it has been successfully applied to predict the efficacy of drugs for breast cancer patients, which can accurately and prospectively guide the individualized treatment of cancer patients in clinical decision-making. Benefit, extend the life cycle, and save the country's precious medical resources."