BOB体育

In the latest development in precision medicine approaches to treating pediatric leukemia, BOB体育 researchers have developed a genetic score to predict patient outcomes with a promising targeted drug treatment.

鈥淭his study advances our development of personalized treatment strategies for leukemia by uncovering how the drug attacks cancer cells differently based on a patient鈥檚 genetics,鈥� said , associate dean for research and graduate education and a professor in the , and lead author of the study, published in the American Association for Cancer Research journal Clinical Cancer Research. 鈥淏y uncovering more about how genetic differences affect responses to novel treatments, we can target new drugs to the patients who are most likely to have the greatest clinical benefit.鈥�

Acute myeloid leukemia, or AML, is the second most common form of childhood leukemia and is among the childhood cancers with the worst prognosis. While intensive chemotherapy and hematopoietic stem cell transplantation are still the mainstay of AML therapy, targeted therapies such as monoclonal antibodies and small-molecule inhibitors have emerged as promising approaches. One of these targeted therapies is an anti-leukemic drug called gemtuzumab ozogamicin, or GO.

Lamba鈥檚 team previously discovered that a genetic variation affects how GO binds and enters cells, determining how patients respond to the drug. In the new study, the team explored how genetic variations affect the way the drug works inside the cell. For the first time, the researchers homed in on a specific component of GO called calicheamicin, the component that plays the most critical role in halting the activities of leukemia cells by triggering DNA damage.

鈥淲e evaluated the genes involved in DNA damage repair pathways for genetic variations that were associated with calicheamicin-induced DNA damage, meaning these genes could predict how effective the drug will be at targeting cancerous cells in different patients,鈥� said Lamba, who serves as co-leader of the BOB体育 Cancer Center鈥檚 research program.

The study included more than 1,200 pediatric patients from the , a National Cancer Institute-supported clinical trials group that is the world鈥檚 largest organization devoted exclusively to childhood and adolescent cancer research.

The researchers used an artificial intelligence strategy to identify the combinations of genetic variants that best predicted outcomes in patients who received standard chemotherapy and GO. Notably, the score was predictive only in patients who received standard chemotherapy with the addition of GO, not in those who received chemotherapy alone, implying its impact is driven by calicheamicin.

鈥淭his indicates the score could have a major impact specific to the use of GO,鈥� Lamba said. 鈥淲e plan to continue our research in a larger group of AML patients to validate our findings and expand this work to address how racial differences affect outcomes. We plan to couple the score with other known prognostic and predictive biomarkers and translate them to clinical use.鈥�

, a postdoctoral associate in Lamba鈥檚 lab, is the study鈥檚 lead author. Lamba collaborated with colleagues at several cancer centers nationwide, including the Fred Hutchinson Cancer Center. Study funding came from the National Institutes of Health, the Leukemia & Lymphoma Society, St. Baldrick鈥檚 Foundation and the National Clinical Trials Network.