Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes

作者：Patrick Kevin Reville, Bofei Wang, Jennifer Marvin‐Peek, Bin Yuan, Yu-Jen Kuo, Araceli Isabella Garza, Jessica Lynn Root, Wei Qiao, Andrea Arruda, Ivo Veletić, Yiwei Liu, Nicholas James Short, Courtney Denton Dinardo, Tapan Mahendra Kadia, Naval Guastad Daver, Philip L. Lorenzi, Koji Sasaki, Steven Mitchell Kornblau, Mark David Minden, Farhad Ravandi, Hagop M. Kantarjian, Hussein A. Abbas · 发表于：Blood · 年份：2025 · DOI：10.1182/blood.2024027244 · 被引用次数：16 · 研究领域：Acute Myeloid Leukemia Research、Hematological disorders and diagnostics、Multiple Myeloma Research and Treatments

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.