Zhaohui Gu, PhD

B-cell acute lymphoblastic leukemia (B-ALL) is the most common cancer in children and remains a leading cause of childhood cancer death. There are different subtypes of B-ALL, and it is important to accurately identify the high-risk subtypes to provide effective treatment. However, it can be difficult to classify B-ALL subtypes because patient samples often have a low amount of leukemia cells. While treatment for B-ALL has been greatly improved, around 20% of patients still relapse and have poor clinical outcomes. In a recent study, we used a technique called RNA-seq to classify B-ALL into over 20 different subtypes. In this project, we will use a more detailed technique called single-cell RNA-seq to classify B-ALL subtypes in samples with different amounts of leukemia cells. This will allow us to identify B-ALL subtypes more sensitively and accurately. Using this single-cell technique, we will also study a particular subtype of B-ALL that is highly resistant to chemotherapy and prone to relapse after treatment. This project aims to show that single-cell analysis can be used to classify B-ALL subtypes in samples with various levels of leukemia cells. This will help doctors to diagnose B-ALL subtypes and track leukemia cells more accurately in clinical settings. We will also be able to identify the specific leukemia cells that cause relapse and study their features at a single-cell level, which will help us understand why relapse happens and find new treatment strategies.