Patrick K Reville, Bofei Wang, Jennifer Marvin-Peek, Bin Yuan, Yu-An Kuo, Araceli Garza, Jessica Root, Wei Qiao, Andrea Arruda, Ivo Veletic, Yiwei Liu, Nicholas J Short, Courtney D DiNardo, Tapan M Kadia, Naval G Daver, Philip L Lorenzi, Koji Sasaki, Steven Kornblau, Mark D Minden, Farhad Ravandi, Hagop M Kantarjian, Hussein A Abbas
{"title":"基于血液的蛋白质组学分析确定OSMR是AML结果的新生物标志物。","authors":"Patrick K Reville, Bofei Wang, Jennifer Marvin-Peek, Bin Yuan, Yu-An Kuo, Araceli Garza, Jessica Root, Wei Qiao, Andrea Arruda, Ivo Veletic, Yiwei Liu, Nicholas J Short, Courtney D DiNardo, Tapan M Kadia, Naval G Daver, Philip L Lorenzi, Koji Sasaki, Steven Kornblau, Mark D Minden, Farhad Ravandi, Hagop M Kantarjian, Hussein A Abbas","doi":"10.1182/blood.2024027244","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>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.</p>","PeriodicalId":9102,"journal":{"name":"Blood","volume":" ","pages":"3015-3029"},"PeriodicalIF":21.0000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226760/pdf/","citationCount":"0","resultStr":"{\"title\":\"Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.\",\"authors\":\"Patrick K Reville, Bofei Wang, Jennifer Marvin-Peek, Bin Yuan, Yu-An Kuo, Araceli Garza, Jessica Root, Wei Qiao, Andrea Arruda, Ivo Veletic, Yiwei Liu, Nicholas J Short, Courtney D DiNardo, Tapan M Kadia, Naval G Daver, Philip L Lorenzi, Koji Sasaki, Steven Kornblau, Mark D Minden, Farhad Ravandi, Hagop M Kantarjian, Hussein A Abbas\",\"doi\":\"10.1182/blood.2024027244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>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.</p>\",\"PeriodicalId\":9102,\"journal\":{\"name\":\"Blood\",\"volume\":\" \",\"pages\":\"3015-3029\"},\"PeriodicalIF\":21.0000,\"publicationDate\":\"2025-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226760/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Blood\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1182/blood.2024027244\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blood","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1182/blood.2024027244","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEMATOLOGY","Score":null,"Total":0}
Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.
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.
期刊介绍:
Blood, the official journal of the American Society of Hematology, published online and in print, provides an international forum for the publication of original articles describing basic laboratory, translational, and clinical investigations in hematology. Primary research articles will be published under the following scientific categories: Clinical Trials and Observations; Gene Therapy; Hematopoiesis and Stem Cells; Immunobiology and Immunotherapy scope; Myeloid Neoplasia; Lymphoid Neoplasia; Phagocytes, Granulocytes and Myelopoiesis; Platelets and Thrombopoiesis; Red Cells, Iron and Erythropoiesis; Thrombosis and Hemostasis; Transfusion Medicine; Transplantation; and Vascular Biology. Papers can be listed under more than one category as appropriate.