Optimization method of EGFR gene E19del mutation digital PCR detection system and detection product

Abstract

The invention relates to an optimization method of a EGFR gene E19del mutation digital PCR detection system, wherein the detection system includes upstream primers, downstream primers, wild-type probes, mutant-type probes, a wild-type template and a mutant-type template; the wild-type template is normal human gDNA after enzyme digestion, and the mutant-type template is a mutant plasmid inserted with a EGFR gene E19del mutant fragment after enzyme digestion; a standard substance is prepared from the mutant-type template and the wild-type template according to a certain proportion of copy number; reaction is performed with a medium mutation frequency standard substance as a template by digital PCR, a data statistical graph is prepared according to the reaction data, and a wild-type fluorescent region and a mutant-type fluorescent region are selected. Reaction is performed with the wild-type template as the template by digital PCR, and the background threshold value is determined. A detection product optimized by the optimization method of the EGFR gene E19del mutation digital PCR detection system has higher accuracy degree.

Description

technical field [0001] The invention relates to a digital PCR detection product for detecting human EGFR gene E19del mutation and an optimization method thereof, and belongs to the field of biotechnology. Background technique [0002] Worldwide, lung cancer is the leading cause of tumor death, seriously endangering human health. About 1.5 million people die from lung cancer every year in the world. The pollution of air pollution, the impact of smoking, etc. all further aggravate the occurrence of lung cancer. The morbidity and mortality of lung cancer rank first among all malignant tumors. Therefore, the early diagnosis and treatment of lung cancer has always been the end point of research and the key to the prevention and treatment of lung cancer. [0003] The EGFR (epidermal growth factor receptor) gene is a driver gene of non-small cell lung cancer (NSCLC) and some lung adenocarcinomas. Tumor cells with activating mutations in the EGFR gene are sensitive to EGFR tyros...

AI Technical Summary

Problems solved by technology

Therefore, through the first generation sequencing and qPCR detection methods, it is impossible to sensitively obtain the mutation information of the tumor somatic cells contained therein.

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