Translational Research and Personalized Medicine
Although precision treatment strategies have been achieved with cancers such as chronic myeloid leukemia, which develop and can be targeted through a single driver event, most cancers are extremely heterogeneous and result from complex genetic changes. Thus, newer, targeted therapies often have limited efficacy in broader patient populations, or the duration of response is short, as drug resistant subclones are selected for and eventually cause disease recurrence. Future cancer drug development is therefore dependent on being able to identify responding and non-responding patients, and effectively monitor and change treatment as the patient’s disease evolves.
For our research, we use a systems-wide approach to analyze samples from individual patients diagnosed with a hematological malignancy. By combining genomic, transcriptomic, proteomic and functional ex vivo drug sensitivity testing of the patient’s tumor cells and comparing these data to that of normal cells, we get a broad view of genomic and phenotypic changes that have occurred in the tumor and which could potentially be therapeutically targeted. In addition, we analyze samples acquired at different stages of the patient’s disease (e.g. diagnosis, during treatment response and relapse) for better insight of disease progression mechanisms and understanding the impact of therapy on the patient’s tumor. Working closely with the FIMM Technology Centre and our collaborators, we quickly return our results to the clinic to maximize the amount of data available for guiding treatment decision of patients with relapsed or refractory disease.
Acute myeloid leukemia (AML)
AML is the most common acute leukemia in adults. However, the standard of care has remained unchanged for the past 30 years. Approximately 50% of AML patients will relapse, at which point there are few treatment options, rapid disease progression and short survival. Recent large-scale genomic studies have shown that AML is comprised of several different diseases, each with separate driver events, and in need of individualized treatment strategies. Deep molecular profiling of AML patient samples combined with functional assessment and clinical outcome data provides us with a wealth of information that we can use to identify novel treatments, identify indicators of response, and understand the impact of genomic changes on treatment response.
Several new drugs have been approved for the treatment of multiple myeloma, extending the lives of many patients. However, the disease is still considered incurable, as patients will often suffer from successive relapses and finally refractory disease. By applying our systems medicine approach to myeloma, we can stratify patients based on their ex vivo drug sensitivity profile, identify novel treatments for relapsed/refractory and high-risk patients, and look for new targets for therapeutic development.