Epigenomic Determinants of Clonal Evolution and Therapy Resistance in Acute Myeloid Leukemia

Going beyond genomics to explore the hidden layers of leukemia resistance 

Acute Myeloid Leukemia (AML) is a rare and highly aggressive form of blood cancer that affects over a thousand Canadians every year. Despite the emergence of new therapies that help control the disease in its early stages, most patients with AML eventually experience a relapse, leading to a low five-year survival rate below 30 per cent. 

These relapses are driven by cells that manage to evade therapy and fuel recurrence. But while researchers have studied the genome of these cells to better understand the mutations that cause treatment resistance, the root cause remains undiscovered. 

For Kristi Fourie (BC Cancer Research Institute), the answer may lie not in the DNA itself—but in non-genetic factors, such as epigenetic and transcriptomic changes, that drive therapy resistance. That is why she will use new funding from a 2025 MOHCCN Health Informatics and Data Science Award to explore the epigenomic and transcriptomic changes that allow therapy-resistant cells to evade treatment and drive relapse.  

To do this, Fourie will use a new technology called single-cell sequencing that will allow her to analyze to examine both genetic and non-genetic factors of individual cells. She will also look at samples taken at the time of diagnosis, and compare them to samples taken at relapse, allowing her to gain insight into the changes in individual cells over time. 

“This research focuses on unraveling the mechanisms of therapy resistance by leveraging advanced single cell sequencing technologies to examine both genetic and non-genetic factors,” explains Fourie.  

By analyzing patient samples taken at both diagnosis and relapse, she will use advanced single-cell technologies to track how different leukemic clones evolve under treatment pressure. Her aim is to pinpoint the distinct features of resistant cell populations—molecular signatures that could one day be used to predict treatment failure or even reprogram cells to become more responsive to therapy. 

“The ultimate goal is to provide a comprehensive understanding of AML progression and relapse and use these insights to identify biomarkers that predict treatment outcomes and guide personalized therapeutic strategies,” she said. 

Funding envelope 

As part of the Health Informatics and Data Science Award, Fourie will receive $40k over the next year from the Network, which is matched by her host institution for a total envelope of $80k. 

“Contributing to cancer research has been a lifelong aspiration, and receiving this award represents a significant milestone on that path,” said Fourie. “I’m incredibly honored to be recognized and supported in work that I believe has the potential to make a meaningful impact. This project is not only scientifically exciting, but also deeply important—both personally and for the broader goal of advancing cancer care.” 

Her mentor, Dr. Aly Karsan, underscored the promise of the project: 
“This project is designed to understand the epigenomic landscape in independent genetic clones in acute myeloid leukemia patients. It has the potential to have a profound impact on divulging the underlying mechanisms of treatment resistance in a rare but highly aggressive leukemia.”