Abstract
Acute lymphoblastic leukemia is the most common pediatric cancer. Fortunately, survival rates exceed 90%, however, infectious complications remain a significant issue that can cause reductions in the quality of life and prognosis of patients. Recently, numerous studies have linked shifts in the gut microbiome composition to infection events in various hematological malignances including acute lymphoblastic leukemia (ALL). These studies have been limited to observing broad taxonomic changes using 16S rRNA gene profiling, while missing possible differences within microbial functions encoded by individual species. In this study we present the first combined 16S rRNA gene and metagenomic shotgun sequencing study on the gut microbiome of an independent pediatric ALL cohort during treatment. In this study we found distinctive differences in alpha diversity and beta diversity in samples from patients with infectious complications in the first 6 months of therapy. We were also able to find specific species and functional pathways that were significantly different in relative abundance between samples that came from patients with infectious complications. Finally, machine learning models based on patient metadata and bacterial species were able to classify samples with high accuracy (84.09%), with bacterial species being the most important classifying features. This study strengthens our understanding of the association between infection and pediatric acute lymphoblastic leukemia treatment and warrants further investigation in the future.