Yan Sun:
Clinical applications of next generation sequencing technology

Date: 28-02-2018    Supervisor: Karsten Kristiansen



Next generation sequencing technology (NGS) features high throughput and low cost of sequencing. The capacity of NGS develops fast, especially with the improvement of read length, read accuracy and the immergence of small-sized machines, making it a powerful genetic testing tool.

In this thesis, I aim to explore the possibility of using next generation sequencing technology in clinical testing. The aim of the first part is to explore NGS in the clinical diagnosis of Mendelian diseases. We developed an approach for target region sequencing of monogenic disorders, which could identify all kinds of variations at a time. We also evaluated the performance of this method for the diagnosis of monogenic disorders in real clinical setting. Our study demonstrated that targeted next generation sequencing could be used in the screening and diagnosis of monogenic disorders with high accuracy and sensitivity.

With the development of personalized therapy, characterization of tumour specific genetic alterations becomes more and more important for the treatment of cancer patients. The aim of the second part of the thesis is to use targeted NGS in the characterization of clinically targetable alterations in patients with cancer. In this part of the thesis, first we introduced a novel algorism which could be used to design cancer specific selector with high specificity using COSMIC and ICGC datasets. Then, we developed a method to detect clinically targetable alterations in lung cancer patients. We also evaluated the performance of this method for the detection of clinically targetable alterations in real clinical setting. Our findings demonstrated that targeted NGS technology is a timely, high throughput, and costeffective method in the detection of multiple mutations simultaneously in various genes.

In a word, targeted next generation sequencing technology is an ideal method to be wildly used in real clinical setting, and has great potential in personalized medicine.