Childhood Cancer

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Genetic Ancestry and Acute Leukemia Outcomes

Institution: 
Baylor College of Medicine
Researcher(s): 
Sydney Burke
Grant Type: 
POST Program Grants
Year Awarded: 
2020
Type of Childhood Cancer: 
Leukemia, Acute Lymphoblastic Leukemia (ALL)
Project Description: 

Mentor: Dr. Philip Lupo

Pediatric leukemia survival rates have improved exponentially; however, relapse remains a leading cause of treatment failure and poor outcomes for children diagnosed with acute lymphoblastic leukemia (ALL). Recent studies have reported disparities among patients regarding survival outcomes: most notably, Hispanic children have both a high incidence of leukemia and poorer outcomes after diagnosis. Data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute demonstrate that Hispanic children with acute leukemia are nearly twice as likely to relapse compared to Non-Hispanic white children. Further, the role of Native American (NA) genetic ancestry in poorer outcomes among Hispanics with ALL is becoming more evident. Recent studies have reported that increased NA ancestry was associated with increased risk of ALL relapse, and importantly, NA genetic ancestry was predictive of relapse independent of minimal residual disease (MRD) status. There is a need for further research exploring the role of genetic ancestry in relation to MRD status and incidence of relapse in children with ALL. As part of the Reducing Ethnic Disparities in Acute Leukemia (REDIAL) Consortium, this project will evaluate the contribution of ancestry-related genetic variation to build risk prediction models for adverse treatment outcomes among children undergoing therapy for acute leukemia and their long-term prognosis. Accurately assessing risk is crucial to tailor therapy and control adverse outcomes. Risk prediction models provide an important approach to assessing outcome by identifying individuals at high risk, facilitating the design and planning of clinical trials, fostering the development of benefit-risk indices, and enabling estimates of burden and cost. Risk prediction models also may aid in the evaluation of treatments and interventions. The ultimate goal of this project is to further investigate the genetic ancestry of children diagnosed with acute leukemia and its role in MRD status as well as incidence of relapse, in an effort to improve overall outcomes.