Leukemia stem cells (LSCs) are linked to relapse in acute myeloid leukemia (AML). The LSC17 gene expression score robustly captures LSC stemness properties in AML and can be used to predict survival outcomes and response to therapy, enabling risk-adapted, upfront treatment approaches. The LSC17 score was developed and validated in a research setting. To enable widespread use of the LSC17 score in clinical decision making, we established a laboratory-developed test (LDT) for the LSC17 score that can be deployed broadly in clinical molecular diagnostic laboratories. We extensively validated the LSC17 LDT in a College of American Pathologists/Clinical Laboratory Improvements Act (CAP/CLIA)-certified laboratory, determining specimen requirements, a synthetic control, and performance parameters for the assay. Importantly, we correlated values from the LSC17 LDT to clinical outcome in a reference cohort of patients with AML, establishing a median assay value that can be used for clinical risk stratification of individual patients with newly diagnosed AML. The assay was established in a second independent CAP/CLIA-certified laboratory, and its technical performance was validated using an independent cohort of patient samples, demonstrating that the LSC17 LDT can be readily implemented in other settings. This study enables the clinical use of the LSC17 score for upfront risk-adapted management of patients with AML.
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http://dx.doi.org/10.1182/bloodadvances.2021005741 | DOI Listing |
Blood Adv
September 2024
Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Equipe Labellisée Ligue 2020, Marseille, France.
Front Cell Dev Biol
March 2024
Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Previous studies have reported that genes highly expressed in leukemic stem cells (LSC) may dictate the survival probability of patients and expression-based cellular deconvolution may be informative in forecasting prognosis. However, whether the prognosis of acute myeloid leukemia (AML) can be predicted using gene expression and deconvoluted cellular abundances is debatable. Nine different cell-type abundances of a training set composed of the AML samples of 422 patients, were used to build a model for predicting prognosis by least absolute shrinkage and selection operator Cox regression.
View Article and Find Full Text PDFHemasphere
December 2023
State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Lysine methyltransferase 2A-rearranged acute myeloid leukemia (-r AML) is a special entity in the 2022 World Health Organization classification of myeloid neoplasms, characterized by high relapse rate and adverse outcomes. Current risk stratification was established on the treatment response and translocation partner of . To study the transcriptomic feature and refine the current stratification of pediatric -r AML, we analyzed clinical and RNA sequencing data of 351 patients.
View Article and Find Full Text PDFBlood Adv
August 2023
CNRS, INSERM, CHU Lille, UMR9020-U1277 - Cancer Heterogeneity Plasticity and Resistance to Therapies, University of Lille, Lille, France.
Whether the LSC17 gene expression can improve risk stratification in the context of next generation sequencing-based risk stratification and measurable residual disease (MRD) in patients with intensively treated AML has not been explored. We analyzed LSC17 in 504 adult patients prospectively treated in the ALFA-0702 trial. RUNX1 or TP53 mutations were associated with higher LSC1 scores while CEBPA and NPM1 mutations were associated with lower scores.
View Article and Find Full Text PDFBr J Haematol
April 2023
Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan.
Leukaemic stem cell (LSC) gene expression has recently been linked to prognosis in patients with acute myeloid leukaemia (17-gene LSC score, LSC-17) and myelodysplastic syndromes. Although chronic myelomonocytic leukaemia (CMML) is regarded as a stem cell disorder, the clinical and biological impact of LSCs on CMML patients remains elusive. Making use of multiple independent validation cohorts, we here describe a concise three-gene expression signature (LSC-3, derived from the LSC-17 score) as an independent and robust prognostic factor for leukaemia-free and overall survival in CMML.
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