In Silico analysis and prediction of novel pharmacogenomic markers of pediatric ALL treatment

Acute lymphoblastic leukemia (ALL) is the most common childhood neoplasm. Side effects of therapy occur in 75% of patients and 1-3% of patients have a lethal outcome due to treatment. More efficient treatment of pediatric ALL has been developed by avoiding drug adverse effects included in the treatment protocols. Therefore, implementation of pharmacogenomics is paramount in pediatric ALL treatment. Next generation sequencing (NGS) contributed to discovery of novel genetic markers, potential candidates for targeted therapy and predictors of efficacy and toxicity of drugs. We aimed to discover novel potential pharmacogenomic markers in pediatric ALL. DNA samples from bone marrow of 17 pediatric ALL patients were analyzed using the platform TruSeq Amplicon – Cancer Panel (Ilumina) for somatic mutations in 48 oncogenes. DNA samples from blood of 100 individuals, using the platform TruSightOne (Ilumina), were analyzed for germinative mutations. An in-house virtual panel for GC response markers was designed. Predicting the effects of novel variants was performed using the SIFT, PolyPhen-2 and PROVEAN software tools. For protein structure stability and modeling we used STRUM method and i-TASSER server. In the NGS study of somatic mutations in pediatric ALL, 9 novel variants have been identified. Bioinformatic analysis has shown that STK11 c.1023G>T and ERBB2 c.2341C>T possess potential as pharmacogenomic markers, therefore, they are candidates for molecular targeted therapy. In the exome sequencing study, according to the prediction algorithms, 3 new potential markers in pharmacogenes related to GC response have been identified, ABCB1 c.947A>G, NCOA3 rs138733364 and TBX21 rs14059812. Using NGS analysis and prediction algorithms, we have detected 2 novel somatic mutations, candidates for targeted molecular therapy, as well as 3 novel germinative variants, potential pharmacogenomic markers of GC response in pediatric ALL. Pharmacogenomic profiling of each pediatric ALL patient is indispensable for new therapy approaches and it could lead to better outcomes.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202