Identification of predictive genetic signatures of Cytarabine responsiveness using a 3D acute myeloid leukaemia model. Issue 10 (26th August 2019)

• Record Type: Journal Article
• Authors: Xu, Haiyan; Muise, Eric S.; Javaid, Sarah; Chen, Lan; Cristescu, Razvan; Mansueto, My Sam; Follmer, Nicole; Cho, Jennifer; Kerr, Kimberley; Altura, Rachel; Machacek, Michelle; Nicholson, Benjamin; Addona, George; Kariv, Ilona; Chen, Hongmin
• Is Part Of: Journal of cellular and molecular medicine. Volume 23:Issue 10(2019)
• Page Start: 7063
• Page End: 7077
• Publication Date: 2019-08-26
• Subjects: 3D culture -- acute myeloid leukaemia -- gene fusion -- RNASeq -- whole‐exome sequencing; Cytology; Medicine; Molecular Biology; Cytologie -- Périodiques; Médecine -- Périodiques; Biologie moléculaire -- Périodiques; Cytology -- Periodicals; Medicine -- Periodicals; Molecular biology -- Periodicals; 611.01805
• DOI: 10.1111/jcmm.14608
• Languages: English
• ISSNs: 1582-1838

Abstract

Abstract: This study reports the establishment of a bone marrow mononuclear cell (BMMC) 3D culture model and the application of this model to define sensitivity and resistance biomarkers of acute myeloid leukaemia (AML) patient bone marrow samples in response to Cytarabine (Ara‐C) treatment. By mimicking physiological bone marrow microenvironment, the growth conditions were optimized by using frozen BMMCs derived from healthy donors. Healthy BMMCs are capable of differentiating into major hematopoietic lineages and various types of stromal cells in this platform. Cryopreserved BMMC samples from 49 AML patients were characterized for ex vivo growth and sensitivity to Ara‐C. RNA sequencing was performed for 3D and 2D cultures to determine differential gene expression patterns. Specific genetic mutations and/or gene expression signatures associated with the ability of the ex vivo expansion and response to Ara‐C were elucidated by whole‐exome and RNA sequencing. Data analysis identified unique gene expression signatures and novel genetic mutations associated with sensitivity to Ara‐C treatment of proliferating AML specimens and can be used as predictive therapeutic biomarkers to determine the optimal treatment regimens. Furthermore, these data demonstrate the translational value of this ex vivo platform which should be widely applicable to evaluate other therapies in AML.