B-cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. There are different subtypes of B-ALL, and it is important to correctly identify the subtype to provide optimal treatment. However, it can be difficult to classify B-ALL subtypes because patient samples often have low amounts of leukemia cells. While treatment for B-ALL has been greatly improved, up to 20% of patients still relapse and their cure rate is still below 50% despite novel treatments. However, it is still not clear why certain subtypes of B-ALL are more resistant to the treatment.
In a recent study, we used a technique called RNA-seq to study the overall gene expression information of leukemia in a large group of B-ALL patients. We were able to classify the patients into over 20 different subtypes. In this new project, we will use a 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 sensitively classify B-ALL subtypes in samples with different levels of leukemia cells. This will help doctors to diagnose B-ALL subtypes more accurately in clinical settings. We will also be able to identify the specific leukemia cells that cause relapse and study their features, which will help us to find new treatment strategies.