Accompanying diagnosis model based on a PDX or PDC model drug sensitivity experiment and multi-omics detection analysis and application

Abstract

The invention provides an accompanying diagnosis model based on a PDX or PDC model drug sensitivity experiment and multi-omics detection analysis, a construction method and application. The method comprises four modules of construction of a human tumor cell line model and an animal transplantation model, a drug sensitivity experiment based on the human tumor cell line model and the animal transplantation model, acquisition of multi-omics data of a human tumor sample, and mining analysis of drug sensitivity phenotype-multi-omics data. The invention provides an implementation thought and a key method of the four modules, and reasonable design of correlation and matching among the four modules, and a whole set of integration strategy of model construction, drug sensitivity experiments, omicsdata acquisition, data integration and data mining analysis is formed. According to the method, the limitation of technical means of an existing accompanying diagnosis scheme research and developmentstrategy in the links of sample planning, data acquisition, data analysis and the like is overcome, accompanying diagnosis scheme research and development can be carried out more flexibly and more widely, and meanwhile mechanism interpretation clues related to markers are obtained.

Description

technical field [0001] The invention belongs to the field of biomedical technology, and relates to a research and development strategy for a companion diagnostic program, which specifically integrates cell and animal model construction, drug sensitivity experiments, multi-omics data acquisition, and related data integration and analysis methods. Background technique [0002] Cancer is a serious public health problem worldwide. According to the data released by the International Agency for Oncology Research, about 8 million people worldwide die of cancer every year, making it the number one cause of death for human beings. Practice has proved that the commonly used mouse spontaneous mutation tumor models, mouse compound mutagenesis tumor models, tumor cell line models, cell line transplantation tumor models, etc., cannot well simulate the biological characteristics of tumor lesions in patients. Anticancer drugs that have good performance in the laboratory stage often fail to...

AI Technical Summary

Problems solved by technology

At the same time, the existing markers based on serum biochemical immune detection are limited by their technical platforms and detection targets, and cannot find key combinations from the complex genetic background and heterogeneity of tumors, making it difficult to use them as companion diagnostic solutions for anti-tumor drugs

Images