Multiomic Analysis Identifies Survival Predictors in African American Patients with Acute Myeloid Leukemia

Medical Laboratory Science Genetics Hematology Life Sciences Immunology Oncology Medicine Cell Biology
acute myeloid leukemia African American gene mutations inflammation survival predictors genomic analysis multiomic study

Multi-omics Analysis Reveals Predictors of Survival in African American AML Patients

Background and Objectives

Acute Myeloid Leukemia (AML) is a hematologic malignancy characterized by clonal expansion of myeloid progenitor cells driven by genomic alterations. Despite advances in genomic profiling, studies focusing on diverse ancestral populations remain scarce. African American patients constitute only 2% of genomic AML studies, despite representing 9% of AML cases. This underrepresentation limits the equitable application of precision medicine and may exacerbate treatment disparities.

Previous studies indicate poorer survival outcomes for African American AML patients, attributed to structural racism, socioeconomic factors, and genomic differences. Current molecular risk stratification systems, primarily based on European ancestry data, may fail to capture ancestry-specific genomic features. This study aims to identify genomic predictors and optimize risk stratification systems for African American AML patients using multi-omics analysis.

Research Origin and Authors

This study, led by researchers from The Ohio State University Comprehensive Cancer Center, was a collaborative effort involving institutions across the US, Nigeria, and South Africa. The findings were published in Nature Genetics in November 2024 under the title, “Multiomic profiling identifies predictors of survival in African American patients with acute myeloid leukemia”.

Methods

  1. Sample Collection and Analysis:

    • The study analyzed 100 AML patients with confirmed African ancestry, comparing them with 323 European ancestry patients.
    • Whole-exome sequencing (WES) and RNA sequencing (RNA-seq) were utilized alongside clinical and treatment data.

  2. Data Processing:

    • High-coverage WES was conducted on tumor and paired normal samples to identify somatic mutations.
    • RNA-seq data enabled gene expression-based clustering and inflammation scoring (Iscore).
    • Single-cell RNA sequencing (scRNA-seq) and CITE-seq identified cell type distributions and pathway activations in NPM1-mutated patients.

  3. Mutation Frequency and Differential Analysis:

    • The study compared mutation frequencies between African and European ancestry groups, identifying novel mutations and functional impacts.

  4. Clinical Outcome Analysis:

    • Survival outcomes and treatment responses were compared under identical therapeutic protocols.
    • The 2022 European LeukemiaNet (ELN) genetic risk stratification system was evaluated for its applicability to African American patients.

Key Findings

  1. Genomic Features and Novel Mutations:

    • 162 recurrently mutated genes were identified in African ancestry patients, with 73% being rare or undetected in European ancestry patients.
    • A previously unreported PHIP mutation was found in 7% of African ancestry patients but only 0.3% of European ancestry patients.

  2. Ancestry-Related Inflammatory and Transcriptomic Profiles:

    • African ancestry patients with NPM1 mutations showed higher inflammation scores compared to their European counterparts (69% vs. 45%).
    • Significant transcriptomic differences were observed in several mutated genes between ancestry groups, indicating distinct AML molecular features.

  3. Mutations and Clinical Outcomes:

    • Multivariable analysis revealed NPM1 and NRAS mutations as adverse prognostic factors for disease-free survival (DFS) in African ancestry patients.
    • IDH1 and IDH2 mutations were linked to reduced overall survival (OS) exclusively in African ancestry patients.

  4. Risk Stratification System Optimization:

    • The current ELN risk system inadequately stratified African ancestry patients, leading to suboptimal risk predictions.
    • Incorporating NPM1, NRAS, and IDH1/IDH2 mutations as adverse markers significantly improved risk stratification for African ancestry patients.
    • This adjustment reclassified 34% of African ancestry patients into the adverse-risk group, informing treatment strategies such as alternative chemotherapy or allogeneic stem cell transplantation.

Significance and Impact

  1. Clinical Applications:

    • This study emphasizes the need for ancestry-specific molecular features in AML risk stratification systems to enhance treatment precision for African ancestry patients.
    • The revised stratification model facilitates more effective therapeutic decisions, including frontline regimen optimization.

  2. Foundational Research:

    • The identification of transcriptomic and cellular distribution differences in NPM1-mutated patients highlights new avenues for AML biological research.

  3. Social and Ethical Implications:

    • The study underscores the importance of addressing structural racism and health disparities in genomic research and clinical care.

Future Directions

This study sets a precedent for ancestry-focused molecular research in AML. Prospective research should validate the clinical utility of the revised risk stratification system and explore the broader impact of genetic ancestry on AML pathogenesis. Large-scale genomic initiatives are needed to ensure equitable representation of diverse populations in cancer research and treatment.