Method for constructing lung cancer multi-gene mutation library

Abstract

The invention discloses a method for constructing a lung cancer multi-gene mutation library. The method can realize mutation of 1435 somatic cells of human genes EGFR, K-ras, B-raf, N-ras, PIK3CA, c-MET, TP53, c-Kit, PDGFRA, ALK, ROS1, RET, ERBB2, NTRK1 and NTRK3. The method can individually manage multiple target sequences and fast finish library construction. The whole library construction process is finished in 2-3h and the manual operation time is only 45min. The method can be used for Illumina and Ion torrent platforms. Through combination of the method and a high-throughput sequencing platform, the problem that a small amount of paraffin tissue slices and peripheral blood samples of a lung cancer patient need multi-gene and multi-target detection of somatic cells is solved and a costis low.

Description

technical field [0001] The invention relates to a method for constructing a lung cancer multi-gene mutation library for high-throughput sequencing detection. Background technique [0002] In 2015, China is expected to have 4.292 million new cancer cases and 2.814 million deaths. Lung cancer is the tumor with the highest incidence rate and the leading cause of cancer death. Gastric cancer, esophageal cancer and liver cancer are common tumors with higher morbidity and mortality in my country. [0003] Traditional methods of cancer treatment include surgery, chemotherapy, and radiotherapy. With the advancement of medical technology, targeted drug treatment of advanced lung cancer has increasingly become a new way, and the treatment varies according to the type of disease. Cancer patients with different driver gene types must be treated differently in treatment. For patients with targets, targeted therapy can be given priority. Targeted therapy and chemotherapy are complete...

AI Technical Summary

Problems solved by technology

[0087] Existing tumor gene detection mainly uses fluorescent quantitative PCR method, which has low detection throughput. For multi-gene and multi-target detection, the cost is high and the sample size is large, resulting in high clinical fees and insufficient sample size.

At present, the industry-recognized gold standard for gene mutation detection is the Sanger sequencing method. This type of technology is complex to operate, has low throughput, low sensitivity, and has a certain risk of missed detection. It is difficult to meet the detection needs of a large number of tumor patients.

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