Acute lymphoblastic leukemia, known as ALL, is one of the most common cancers occurring in childhood. Even though chemotherapy is very effective in treating the disease, it leads to significant side effects that impact children later in life. As a result, the need for an alternative therapy is pressing – and Jan Cools (VIB-KU Leuven Center for Cancer Biology) accepted the challenge, with high-impact results published in Cancer Discovery. We asked Jan and team members Charles de Bock and Sofie Demeyer, both Postdocs, for more details.
ALL develops when gene mutations cause blood-borne immune cells to transform into aggressive leukemia cells. However, many of the mutations seen in the disease occur in specific gene pathways, called JAK3/STAT5 and HOXA9. Jan and his international team of researchers used multiple sequencing technologies to observe the interaction between these two genes, discovering that HOXA9 boosts the effects of JAK3/STAT5 mutations, which in turn causes leukemia to develop even more rapidly and aggressively in patients with both mutations.
Sofie, can you describe the biggest challenges you ran into while performing this research?
Sofie: “There were some big computational challenges that came with this project. We had to combine different types of sequencing data, and linking RNA-seq, ChIP-seq and ATAC-seq data was not as straightforward as we expected. Even more, we had data from different models and conditions, and it was tough to ensure that we were comparing the data correctly.
Moreover, optimizing the ChIP-seq protocol and finding the right antibodies required a lot of analyses. I think we analyzed about twice as much sequencing data than was actually described in the paper to get to ChIP signals that we were convinced could be trusted.”
Charles, in your opinion, what was the fulfilling aspect of this study?
Charles: “This research highlights the power of using genomic sequencing data from patients to identify potentially cooperating mutations and then functionally testing them using in vivo mouse models. On that note, one of the interesting aspects of this project was to creatively find a novel solution to limit transgene expression within a specific blood lineage. We tested a few different published strategies, but it was our own method that worked the best, which was very fulfilling. This new method is now being used in several ongoing projects.
It was also inspiring to witness the great teamwork executed by a dedicated group of postdocs, PhD students and technicians to overcome numerous technical challenges. As Sofie said, generating informative ChIP-seq data from patient samples took a lot of effort.”
Jan, how has your leukemia research evolved over the years?
Jan: “Fifteen years ago, our team identified and characterized a specific kinase as the cause of chronic eosinophilic leukemia – a generally long-term and subacute cancer. Today, patients suffering from this type of leukemia can be cured using the inhibitor of the kinase that we identified.”
Why do you undertake this research, and what do you think are the future next steps to better target ALL with new therapies?
“It’s extremely rewarding to work on research questions that can lead to the development of new therapies for important diseases such as cancer. Acute lymphoblastic leukemia is rare, but it’s important to me, since it severely affects the lives of children and young adults. It’s also a much more complicated cancer than chronic eosinophilic leukemia and involves many different mutations.
That being said, I’m convinced that by making better mouse models that we can use to study the cooperation between different oncogenic events, we will find a way to target these leukemia cells.”
De Bock et al, Cancer Discovery 2018