Multiomic profiling identifies predictors of survival in African American patients with acute myeloid leukemia

Andrew Stiff1, Maarten Fornerod2, Bailee N Kain3

  • 1The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.

Nature Genetics
|October 4, 2024
PubMed

Insights

Genomic analysis reveals distinct mutation profiles in Black patients with acute myeloid leukemia (AML). Incorporating ancestry-specific markers improves risk stratification and outcome prediction for this understudied population.

Area of Science:

  • Genomics
  • Hematology
  • Cancer Research

Background:

  • Genomic profiles and prognostic biomarkers in acute myeloid leukemia (AML) are underexplored in diverse populations.
  • Limited data exists on genetic variations and their impact on AML outcomes in patients of African ancestry.

Purpose of the Study:

  • To analyze genomic profiles and identify prognostic biomarkers in Black patients with AML.
  • To compare mutation frequencies between Black and white patients with AML.
  • To evaluate the impact of ancestry-specific markers on risk stratification and outcome prediction.

Main Methods:

  • Exome and transcriptome analysis of 100 Black patients with AML (Alliance cohort).
  • Comparison of somatic mutation frequencies with 323 white patients with AML (BeatAML cohort).
  • Multivariable analyses to identify prognostic markers and assess risk stratification.

Main Results:

  • 73% of gene mutations recurrent in Black patients were rare or absent in white patients.
  • A novel PHIP alteration was identified in 7% of Black patients.
  • NPM1 and NRAS mutations correlated with inferior disease-free survival; IDH1/IDH2 mutations with reduced overall survival in Black patients.
  • Significant differences in inflammatory profiles, cell types, and transcriptional profiles were observed between Black and white patients with NPM1 mutations.
  • Ancestry-specific risk markers altered risk group assignment for one-third of Black patients, improving outcome prediction.

Conclusions:

  • Genomic landscapes of AML differ significantly across ancestral backgrounds.
  • Ancestry-specific prognostic markers are crucial for accurate risk stratification and improved outcome prediction in AML.
  • Further research into the unique biological and clinical characteristics of AML in diverse populations is warranted.