Integrated m6A reader network in acute myeloid leukemia: prognostic modeling, immune modulation, and functional...

Area of Science:

• Molecular Biology
• Cancer Research
• Immunology

Background:

• RNA N6-methyladenosine (m6A) modifications are crucial in cancer, but their role in acute myeloid leukemia (AML) is not fully understood.
• The specific contributions of m6A readers to AML pathogenesis and patient outcomes require further investigation.

Purpose of the Study:

• To elucidate the collective roles of m6A readers in AML development and prognosis.
• To develop a prognostic tool and identify therapeutic targets within the m6A reader network.

Main Methods:

• Leveraged multiomics data from 2680 AML patients to map the m6A reader network.
• Developed a m6A reader activity score (m6ARS) and a 28-gene prognostic model using machine learning.
• Performed functional studies to investigate the oncogenic role of YTHDF3.

Main Results:

• Identified coordinated upregulation of m6A readers associated with aggressive AML subtypes and poor prognosis.
• Elevated m6ARS correlated with increased proliferation, reduced CD8+ T cell infiltration, and immune evasion.
• The 28-gene model accurately predicted patient outcomes across multiple cohorts, outperforming traditional factors.
• YTHDF3 was identified as an oncogenic driver, promoting AML by stabilizing key transcripts.

Conclusions:

• The m6A reader network is a key regulator of AML progression and immune evasion.
• The developed prognostic framework and m6ARS offer valuable tools for risk stratification and guiding therapy.
• YTHDF3 represents a promising therapeutic target for AML, linking RNA epigenetics to clinical applications.