Faculty, Staff and Student Publications

Publication Date

6-19-2025

Journal

Blood

DOI

10.1182/blood.2024027244

PMID

40179376

PMCID

PMC12226760

PubMedCentral® Posted Date

4-5-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Inflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathogenesis. We performed blood-based proteomic profiling of 251 inflammatory proteins in 543 patients with newly diagnosed AML. Using a machine learning model, we derived an 8-protein prognostic score termed the leukemia inflammatory risk score (LIRS). Individual proteins were evaluated in multivariable Cox models, and model performance was assessed by cumulative concordance index. Findings were validated in internal and external cohorts across 2 institutions. Blood-based LIRS significantly outperformed the European LeukemiaNet 2022 risk model and was independently prognostic of overall survival after accounting for known clinical and molecular prognostic factors. Oncostatin M receptor was uniquely identified as the strongest independent predictor of survival, early mortality, and induction chemotherapy response, and further validated in an independent assay. These blood-based biomarkers could have significant clinical implications for risk stratification and prognostication in patients with newly diagnosed AML.

Keywords

Humans, Leukemia, Myeloid, Acute, Male, Female, Middle Aged, Proteomics, Biomarkers, Tumor, Aged, Adult, Prognosis, Aged, 80 and over, Young Adult

Published Open-Access

yes

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