December 8, 2025BloodOpen Access

A blood-based protein signature adds to genomic prognostication of survival in TP53-mutated Acute Myeloid Leukemia

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Machine learning reveals a 13-protein signature adds prognostic value for survival in TP53-mutated AML, suggesting new therapeutic approaches.

High-risk TP53-mutated AML patients showed a median overall survival of only 3 months, highlighting the urgent need for better prognostic tools.
Thirteen inflammatory proteins were significantly associated with survival outcomes, deriving a hazard ratio of 3.02 when combined with genomic factors.
Assessment using machine learning on a large protein panel improved risk stratification in TP53-mutated AML beyond traditional methods.
Integrating this protein signature with existing genomic models may guide future therapeutic approaches in managing high-risk AML.

Loghavi et al. (2025) studied this question.

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December 8, 2025BloodOpen Access

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Authors

Machine learning reveals a 13-protein signature adds prognostic value for survival in TP53-mutated AML, suggesting new therapeutic approaches.

High-risk TP53-mutated AML patients showed a median overall survival of only 3 months, highlighting the urgent need for better prognostic tools.
Thirteen inflammatory proteins were significantly associated with survival outcomes, deriving a hazard ratio of 3.02 when combined with genomic factors.
Assessment using machine learning on a large protein panel improved risk stratification in TP53-mutated AML beyond traditional methods.
Integrating this protein signature with existing genomic models may guide future therapeutic approaches in managing high-risk AML.

Loghavi et al. (2025) studied this question.

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