Scientists have discovered new genetic variations that affect the likelihood of relapse in children with standard risk B-cell acute lymphoblastic leukemia (SR B-ALL), which is the most prevalent cancer among children.
Researchers from St. Jude Children’s Research Hospital, Seattle Children’s, and the Children’s Oncology Group (COG) have uncovered new genetic variations that determine the risk of relapse in children with standard risk B-cell acute lymphoblastic leukemia (SR B-ALL), the most common cancer affecting children. The findings on genomic indicators of relapse in SR B-ALL pave the way for better diagnostic methods, precise treatment adjustments, and potentially new treatment options. This study, published today in the Journal of Clinical Oncology, is a significant step forward.
Standard risk ALL typically has excellent outcomes, boasting remission rates above 90%. However, approximately 15% of those who go into remission will experience a relapse. Earlier research on genomic changes to predict relapse risk has mainly concentrated on higher-risk ALL groups. Since SR B-ALL represents a larger patient demographic and makes up roughly half of the childhood ALL relapse cases, this study is one of the first to comprehensively assess the genetic factors influencing relapse risk in SR B-ALL on a substantial scale.
“ALL, being the most frequently diagnosed cancer in children, is a remarkable success, with more than 90% of affected children being cured. Yet, there is still a segment of children whose disease is not completely resolved, and the reasons for this remain unclear,” stated co-senior author Charles Mullighan, MBBS (Hons), MSc, MD, who serves as the Deputy Director of the St. Jude Comprehensive Cancer Center and is part of the Department of Pathology. “This research focused on those poorly understood cases, helping to enlighten us on the factors that influence treatment failure and relapse.”
Unveiling genetic variations that alter risk
Genomic profiling helps identify specific genetic changes related to cancer susceptibility, relapse probabilities, and tumor responses to treatments. Such studies enable scientists and medical professionals to forecast how patients will likely respond to therapy, providing valuable insights that direct the management of childhood ALL. Findings from this collaborative research underscore the significance of genomic profiling in accurately assessing risk in B-ALL alongside traditional evaluation criteria.
“In the future, we aim to lessen standard therapies for children with ALL, as we understand that many can be successfully treated with reduced intervention,” noted co-senior author Mignon Loh, MD, head of Seattle Children’s Cancer and Blood Disorders Center, and director of the Ben Towne Center for Childhood Cancer Research. “It’s crucial to correctly identify these children, and the unique design of this study enabled us to achieve that.”
The researchers carried out genome and transcriptome sequencing on samples from both relapsed SR B-ALL cases and those that remained in complete remission at a ratio of one to two. They found that various ALL subtypes, genetic changes, and patterns of aneuploidy (presence of extra or missing chromosomes) were associated with the risk and timing of relapse. Certain B-ALL subtypes, like hyperdiploid and ETV6::RUNX1 ALL, exhibited a lower relapse rate, whereas others, including PAX5-altered, TCF3/4::HLF, ETV6::RUNX1-like, and BCR::ABL1-like, were linked to a heightened relapse risk. Importantly, the specific genetic alterations within these B-ALL subtypes also affected relapse risk. This study revealed that genetic variations and cancer types significantly impact relapse risk in SR B-ALL, indicating that standard-risk patients could exhibit high-risk tumor characteristics.
“Whole genome sequencing was crucial for accurately and comprehensively detecting these genetic changes, some of which would have gone unnoticed without it,” explained Mullighan. “It is essential for children with SR ALL to have their tumor cell genome sequenced right at diagnosis to determine if their tumor cells possess these high-risk traits, enabling an appropriate adjustment of their initial treatment intensity.”
“In addition to standard therapies, this information could be harnessed to formulate and investigate new personalized treatment strategies,” Loh added.
