Abstract P31: Graph-Based Deep Learning for Predicting Synergy in Multi-Drug Treatments for Leukemia

Leukemia, a cancer impacting blood-forming tissues such as bone marrow and the lymphatic system, presents in various forms, affecting children and adults differently. The therapeutic approach is complex and depends on the specific leukemia type. Effective management is crucial as it disrupts normal blood cell production, increasing infection susceptibility. Treatments like chemotherapy can further weaken immunity. Thus, a patient’s healthcare plan should focus on comfort, reducing chemotherapy side effects, protecting veins, addressing complications, and offering educational and emotional support. One of the greatest challenges we face in cancer research and treatment is the ability of cancer to adapt, evolve, and become drug-resistant. We expect that the future of cancer treatment will be in combining therapies to overcome resistance – but we need to get much better at predicting which drug combinations will work best for individual patients. Recent studies showed that a combination of two drugs keeps patients with chronic lymphocytic leukemia disease-free and alive longer than the current standard of care, according to the Stanford University School of Medicine and multiple other institutions. This article proposes studies on the combined use of drugs for treating leukemia. Employing a mix of medicines might decrease the chances of tumor resistance. Starting multiple drugs concurrently allows for immediate application during disease onset, avoiding delays. Initial chemotherapy uses a drug combination to eliminate maximum leukemia cells and restore normal blood counts. Afterward, intensification chemotherapy targets any residual, undetectable leukemia cells in the blood or bone marrow. To recommend a drug combination to treat/manage Leukemia, we have employed a Graph Neural Network to pass information between these trending drugs and genes that act as potential targets for Leukemia.

Citation Format: Archishma Marrapu. Graph-Based Deep Learning for Predicting Synergy in Multi-Drug Treatments for Leukemia [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P31.