ddPCR detection optimization method of lung cancer EGFR T790M sites and application thereof

Abstract

The invention discloses a ddPCR detection optimization method of lung cancer EGFR T790M sites and application thereof. The detection optimization method comprises the following steps: optimizing the extraction of cfDNA, and performing PCR amplification and probe detection on the cfDNA by use of the mutant type and wild type fluorescence detection probe designed for the T790M gene sites and a specific primer pair for performing specific amplification on a target region; performing data analysis of a detected fluorescence signal value to acquire the accurate EGFR gene T790M sites information. The noninvasive detection can be really realized by only needing a small amount of peripheral blood. The detection optimization method disclosed by the invention performs detection analysis of the important sites related to the lung cancer target medication in the ctDNA, and provides the medication related gene sites mutant information for the lung cancer patient in the late treatment process of the lung cancer, thereby providing the important reference evidence for the personalized accurate medication guidance, the drug efficacy evaluation and therapeutic monitoring.

Description

technical field [0001] The invention relates to the field of gene detection, in particular to a ddPCR detection optimization method and application of EGFR T790M locus in lung cancer. Background technique [0002] Lung cancer is the most common primary malignant tumor of the lung. The vast majority of lung cancers originate from the bronchial mucosal epithelium, so it is also called bronchial lung cancer. Over the past 50 years, the morbidity and mortality of lung cancer have risen rapidly in countries all over the world, especially in industrialized countries, and lung cancer has ranked first among male patients who died of cancer. Lung cancer is the malignant tumor with the highest morbidity and mortality rate in the world. The 5-year survival rate is only 16.8%. Every year, 1.6 million new lung cancer patients are diagnosed. Lung cancer is also the leading cause of death of cancer patients, and 1.4 million people die of lung cancer. In 2015, the American Cancer Society ...

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Problems solved by technology

[0009] To sum up, the existing optimization methods for lung cancer detection have the following defects and deficiencies: First, the traditional detection optimization methods mainly rely on the experience of technicians to interpret the results, which cannot directly and objectively and accurately reflect the detection results, nor can they perform absolute DNA analysis. Quantitative; second, the existing optimized detection method based on lung cancer EGFR T790M usually has high requirements on the total amount and quality of cfDNA in the sample, and the detection of low-quality samples is limited; third, the existing optimized detection method based on lung cancer EGFR T790M The detection steps are cumbersome and the detection sensitivity is low, and there will be a certain amount of false positive detection results, especially in plasma samples, the false positive detection rate of cfDNA is higher, because cfDNA is mainly derived from benign cells of germline origin, and the proportion of ctDNA is relatively Fourth, there are literatures showing that the addition of carrier RNA in the cfDNA extraction process does not increase the total amount of cfDNA extraction, and it is likely to cause large fragments of gDNA to aggregate.

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