Gut Microbiome Composition Predicts Infection Risk During Chemotherapy in Children With Acute Lymphoblastic Leukemia

Hana Hakim1, Ronald Dallas1, Joshua Wolf1

  • 1Department of Infectious Diseases, St Jude Children's Research Hospital, Memphis, Tennessee.

Insights

Gut bacteria composition can predict infections in children with acute lymphoblastic leukemia (ALL). Specific bacterial patterns before and during chemotherapy indicate a higher risk of febrile neutropenia and diarrhea.

Area of Science:

  • Microbiology
  • Pediatric Oncology
  • Gastroenterology

Background:

  • Myelosuppression-related infections are a significant cause of illness and death in pediatric acute lymphoblastic leukemia (ALL).
  • Understanding factors that predict these infections is crucial for improving patient outcomes.

Purpose of the Study:

  • To investigate the role of gut microbiota in predicting infections in children newly diagnosed with ALL.
  • To correlate gut microbiome composition with the incidence of infections during chemotherapy.

Main Methods:

  • Fecal samples were collected from 199 children with newly diagnosed ALL at diagnosis and after chemotherapy phases.
  • Bacterial 16S rRNA gene sequencing was used to analyze gut microbiome diversity and composition.
  • Microbiome data was correlated with infection events, specifically febrile neutropenia and diarrhea.

Main Results:

  • Chemotherapy significantly reduced gut microbial diversity.
  • The relative abundance of certain bacteria like Bacteroidetes decreased, while others like Clostridiaceae and Streptococcaceae increased post-chemotherapy.
  • A baseline gut microbiome rich in Proteobacteria predicted febrile neutropenia.
  • Dominance of Enterococcaceae or Streptococcaceae predicted increased risk of febrile neutropenia and/or diarrhea during subsequent chemotherapy phases.

Conclusions:

  • Gut microbiome alterations during chemotherapy for ALL are linked to infection risk.
  • Proteobacteria at diagnosis and Enterococcaceae/Streptococcaceae dominance during treatment are predictive biomarkers for infections in pediatric ALL patients.
Abstract

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